Last Updated on November 22, 2022
Get Started And Avoid Getting The Wrong Advice
Machine learning is a fascinating and powerful field of study filled with algorithms and data.
The thing is, there are so many different types of people interested in machine learning, and each has different needs. It is important to understand what it is you want from machine learning and to tailor your self-study to those needs.
If you don’t, you could very easily go down the rabbit hole and get lost, lose interest and not get what you’re looking for.
Find Your Tribe!
In this post you will discover the 10 main groups of people interested in machine learning. I call them machine learning tribes.
You will discover the general needs and the types of resources that each tribe will find most valuable.
Importantly, you can review the 10 tribes and discover where you fit, find comfort that there are other people like you and get an idea of what your next steps could be.
Where do you fit? Leave a comment and let me know.
Avoid Tribe Mismatch, It’s Very Common
You’re interested in machine learning. You ask around and a specific course or book is recommended.
A few hours in, you get frustrated but you’re not sure why.
Has this happened to you?
It’s because the resource you picked up is great, it just might not be great for your specific circumstance.
This is a common problem and I call it the problem of mismatch.
Classic Example of the Developer and the Textbook
A classic example is a developer interested in working through a one-off problem. They are recommended a machine learning textbook.
They purchase it, start reading and never make it past the first chapter.
A textbook is perfect for a student in a graduate machine learning class with 4 years of math class in their recent past.
It is next to useless for a developer, 10 years into their career looking at machine learning as a tool to deliver a result.
This is why it is critical to know about the different groups interested in machine learning and to which group you belong. So that you can find other people like you and start using the resources that will actually help you get the solution you’re after.
10 Machine Learning Tribes
In this section we lay out 10 different groups of people interested in machine learning.
I’ve given each name, highlighted their main goals and interests and listed resources that people in that group can use in their next steps. I’ve also grouped the groups by general theme such as business, academic, engineering and data.
There may be some overlap in the groups. It is also possible that you belong to one or more of them. That’s fine (and I’d love to hear about it in the comments).
Also, we are constraining our interest here to machine learning, not all of data science, which is broader.
Let’s dive in.
Here’s a quick snapshot of the 10 tribes:
- Business Tribes
- 1) Business Person with a General Interest
- 2) Manager Interested in Delivering a Project
- Academic Tribes
- 3) Machine Learning Student in a Undergraduate or Graduate Class
- 4) Machine Learning Researcher Interested in Impacting the Field
- 5) General Researcher Interested in Modeling Their Problem
- Engineering Tribes
- 6) Programmer Interested in Implementing Algorithms
- 7) Developer Interested in Delivering One-Off Predictions
- 8) Engineer Interested In Developing Smarter Software And Services
- Data Tribes
- 9) Data Scientist interested in Getting Better Answers to Business Questions
- 10) Data Analyst interested in Better Explaining Data
Generally, these are people interested in harnessing machine learning effectively in their organization, but not necessarily interested in the nuts and bolts of algorithms or tools.
Business people might use terms like business intelligence or predictive analytics, both of which are more general fields that may make use of machine learning techniques.
1) Business Person with a General Interest
This may be anyone from an executive to a consultant who has heard about machine learning and is looking to make use of it strategically, perhaps in upcoming projects or initiatives.
This is not really my area, but some resources that might be useful for more strategic thinking include:
- Gartner’s Magic Quadrant for Advanced Analytics Platforms, 2015
- Gartner’s Machine Learning Drives Digital Business, 2014
- McKinsey’s An executive’s guide to machine learning, 2015
I would also recommend the books in the next section for “Managers“.
2) Manager Interested in Delivering a Project
This is a project manager or similar leadership position on a project in which machine learning is being used. It may be a niche feature of the project or core to the project.
Resources that would be useful would be high-level perspectives on the field that relate various classes of problem and algorithm without going into too much detail.
Check out the following books:
- Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
- Data Science for Business: What you need to know about data mining and data-analytic thinking
- Data Smart: Using Data Science to Transform Information into Insight
Generally, these are people interested in machine learning from an academic perspective. They may be students (undergraduate or postgraduate) or otherwise associated with a university.
Additional examples are post-docs, research associates and lectures of various sorts.
Academic tribes may spend a lot of time researching a specific machine learning algorithm in research papers. You can learn more about researching algorithms in the post “How to Research a Machine Learning Algorithm“.
3) Machine Learning Student in a Undergraduate or Graduate Class
A machine learning student is very likely taking a class and interested in hyper-specific questions related to techniques and algorithms.
A student has the structure to focus and the time to dive deeper into the material. They are best served with a textbook. Some of the best machine learning textbooks are as follows:
- Machine Learning: A Probabilistic Perspective
- Pattern Recognition and Machine Learning
- The Elements of Statistical Learning: Data Mining. Inference. and Prediction
4) Machine Learning Researcher Interested in Impacting the Field
A machine learning researcher is interested in a deep understanding of one aspect of machine learning to the point of making a minor addition to extend the field.
A researcher is interested in research papers, journals and the organizations and networking that go along with them.
Textbooks don’t cut it, they’re secondary sources and out of date.
Some high-profile machine learning journals and proceedings are:
- Journal of Machine Learning Research (JMLR)
- Neural Information Processing Systems (NIPS)
- Knowledge Discovery and Data Mining (SIGKDD)
- International Conference on Machine Learning (ICML)
Checkout the great answers to the Quora question “What are the best conferences and journals about machine learning?“.
Here’s a handy list of the top 50 ranked journals in Artificial Intelligence.
5) General Researcher Interested in Modeling Their Problem
A general researcher may be interested in machine learning, but as a tool. They are most likely interested in building a descriptive or predictive model using their own data.
For example, a scientist from the field of client research, geology, or biology has their own dataset and is looking to create a model in order to make predictions and/or better understand the underlying problem.
They are often less interested in model accuracy and more interested in model explainability. Therefore, simpler well understood methods borrowed from statistics are preferred, such as linear regression and logistic regression.
Nevertheless, good systematic process is desired.
I would recommend the resources under the “Engineering Tribes“, specifically,”Developer Interested in Delivering One-Off Predictions“. Also take a look at the “Data Scientist” group under “Data Tribes“.
Generally, a group of developers that are used to delivering solutions to problems with software and want to incorporate machine learning.
A good general post I recommend for engineers looking to get into machine learning is “Machine Learning for Programmers“.
Engineer Tribes can get a lot of help and support in machine learning communities like those on Q&A sites. For more information, checkout the post “Machine Learning Communities“.
6) Programmer Interested in Implementing Algorithms
An excellent way for a programmer to develop skills in machine learning is to use their existing programming skills and implement machine learning algorithms from scratch.
I talk a lot about this approach and give good tips and resources in my blog post “Understand Machine Learning Algorithms By Implementing Them From Scratch“.
Three books I recommend for this approach taken from that blog post are:
- Data Science from Scratch: First Principles with Python
- Machine Learning in Action
- Machine Learning: An Algorithmic Perspective
7) Developer Interested in Delivering One-Off Predictions
A developer is not necessarily a great programmer, and programming is not required to develop and deliver an accurate and reliable predictive model.
A one-off predictive model may be required in a business environment for the set of predictions it can provide. It is also a powerful model for self-stud, for working through practice datasets and even machine learning competitions.
You can learn a lot by working systematically through a process on a problem and delivering a standalone model.
Checkout my systematic process for working a machine learning problem end-to-end in the post “Process for working through Machine Learning Problems“.
8) Engineer Interested In Developing Smarter Software And Services
An engineer interested in adding machine learning to their software project requires some knowledge of the algorithms, some knowledge of how to work problems end-to-end and knowledge for how to get the algorithm running reliably in an operational environment.
This group of people grow from the previous two groups described and might best be described as a machine learning engineer. They look to use fast algorithms that deliver reliable and accurate results, balancing these concerns.
This group also makes heavy use of machine learning libraries and infrastructure.
Some useful resources on jumpstarting machine learning libraries include:
- Building Machine Learning Systems with Python
- Learning scikit-learn: Machine Learning in Python
- Practical Data Science with R
- Machine Learning with R
Also, checkout the post “Building a Production Machine Learning Infrastructure“.
Generally, this are groups of people that primarily are in data roles but may need to make use of machine learning.
9) Data Scientist interested in Getting Better Answers to Business Questions
The learning does not stop when you’re a data scientist.
You must stay on top of the latest data flows, techniques and algorithms. This includes the machine learning techniques that you need to describe data and create predictive models.
The data scientist can take what they need from the more applied resources listed under “Engineering Tribes“, as well as the more theoretical resources listed under “Academic Tribes“.
Nevertheless, some data science-centric machine learning resources that include this mix are:
- Applied Predictive Modeling
- An Introduction to Statistical Learning: with Applications in R
- Machine Learning for Hackers
10) Data Analyst interested in Better Explaining Data
Data analysts are primarily interested in explaining data in the context of business interests. Sometimes machine learning algorithms are useful for providing more powerful models. Mostly descriptive models, but also sometimes predictive.
Like the group “General Researcher“, this group likely has a good foundation in statistics and statistical inference. Also, given that they are most likely interested in a descriptive model, classical methods like linear and logistic regression may be sufficient. Explainability over accuracy in the resulting model.
Many of the same resources above would be useful, although perhaps with more of a statistical inference stance.
In this post you discovered 10 different groups of people interested in machine learning.
Here’s that handy mind map to summarize the 10 tribes:
Your action step is to review the list and figure out where you belong.
Which group is your tribe? Leave a comment below and let me know.
Great post! Keep up the good work.
Much appreciated Najmuddin.
Thanks Jason, I was very confused between different tribes and different course suggestions. I was feeling confused like where i am going or where i have to go. But after this, i made my mind. I wanted to implement machine learning to build better software solutions and services.
Thanks again brother.
Hi Deepak…Thank you for your support and feedback! We greatly appreciate it!
I’m in group 10. 🙂
Thanks Susan, I wonder if a text like “The Elements of Statistical Learning” would be a good place to start for you?
How about ‘old Windows/VMWare guy tired of maintaining OSs, wanting s more valuable skillset, and needing to stay employed for 15 mores years”? I guess 9.
There are many ways to deliver value with this tool set!
Wow, very inspiring and helpful. You have dissected the machine learning ‘myth’ to bare bones. Now as a relatively new comer? I can identify not path but the resources to work with as well.
Thank ypu Jason.
Your posts are always brilliant by the way….
Thanks, I’m happy it helped!
This is excellent! Very well thought out and communicated. Thank you for all the resources as well!
Hi i belong ti group 8.machine Learning Engineer.
Tnx Mr jason for ur sound, effective & motivated post.
I am in Group-8 – machine learning engineer. That would be a great job title.
Nice one Amit.
Yes, I totally agree!
Thank you, Jason, this is really awesome!
I’m a programmer, I think group 8 fit me well, and for my business, group 9 will help a lot, any advice?
btw, can I translate your blog to Chinese and post to my blog? It definitely will help a lot of people, and I will keep your original link for sure.
Very nice hexcola.
Rather than translate, why not start your own blog and share your machine learning journey!?
Great way to start my ml learning. Really useful to identify yourselves as one of the mentioned tribes. I’m 8! Thanks Jason.
Great! Thanks Viral.
I belong to Tribe-2. But would want to build deep knowledge in Machine learning in next couple of months by implementing/using some of the algorithms. So on the journey of trying few algorithms and learning Python and R now. Your post is very useful. Thanks a lot.
General Researcher Interested in Modeling Their Problem
Im a guy in South Africa and would like to get into machine learning. I do not have an IT background. Is there space in the area of learning for someon with no IT background to develop a career in the field? And what areas can one get into if one gets into business as a ml consultant?
Perhaps Weka is a good place to start Chris:
Excellent Jason! We are a start up on advanced analytics and all of us follow your blog and waiting with lot of interest your mail. Thanks Jason!
I’m in Group 8, but often find myself in Group 3. I am currently entering grad school, and looking forward to taking some courses. More importantly, for my tribe (8), learning ML algorithms and reading papers is a means to an end (building cool things). I’ve found that keeping the end in mind, and being given room to tinker (break things quickly) prevents frustration or boredom.
Jason, this is a fantastic concept! I’m preparing a presentation on instructional design as part of interviewing for IBM Watson Health (keep your fingers crossed for me). To discuss my design process (quite similar to UI design process) I need a context and machine learning seems a good fit. But of course it’s a hugely complex topic and I’m not a programmer, so it’s like pulling a rabbit out of a hat to put together a *very* simple, but accurate story. Your mind map is perfect. I’ll be sure to include a reference to your website in my discussion. Congrats on teaching a maths-avoidant, right-brained baby-boomer mom the basics! Cheers from Boston, MA.
I belongs to groups 6, 7, and 8.
I guess group 9 and 10 suit me the best
I’m a bit of the 3 major groups. I’d pick 1, 5, and 10.
I think I belong to this group too. 1, 5 & 10. How do I get help to jump start my journey?
I’ve been surfing online more than three hours nowadays,
but I by no means discovered any attention-grabbing article like yours.
It is pretty value enough for me. In my view, if all site owners and bloggers made good content as you probably did, the web
will likely be much more useful than ever before.
I belong to 8…try hard to move into 4 & 5…hope someone accepts me as their student!!
Congratulations for explanation about theme! I liked it so much reading that did not even notice the time pass…
Really nice article.
I’m definitely in one of the Engineering tribes. As I’m just getting started, I’m probably place myself in Group 6. But I hope to continue growing my knowledge and gain deeper and deeper understanding in machine learning.
I’m in 8 – Engineer Interested In Developing Smarter Software And Services –
Maybe a quick visualisation of feedback received would be good Jason, just a pie chart as feedback comes in, see who everyone identifies with the most!
I’m in group 9. I am already familiar with many ML approaches but want to have a deeper understanding in order to support my product better. The assumptions (both statistical and practical) of each model plays a crucial part of the decision on which model to invest.
Are there any additional resources besides the three books that people like me would fine relevant?
I hope I gave enough information.
Thanks for the site! It’s excellent!
My book on machine learning algorithms might give you the insight you seek on how the techniques work:
I’m in group 3
I somehow don’t belong to any of the tribe. Because, I am trying to make a career change. I do have an engineering background and with it comes the mathematics background. Also, I have some experience in python (mostly through online courses). Can you help me understand where I belong and how i can proceed?
p.s. I am doing Machine Learning course offered by University of Washington on Coursera.
Thanks, looking forward to learning from you.
Think about why you want to learn machine learning and what you want to be able to do with the skill.
Focus on where you want to be and then associate with that tribe.
Thanks that would help! Just love this site!
Any book or textbook you recommend for someone that is curious about machine learning. But is just exploring or testing the waters right now?
Stat right here Eric:
I am in group 8. Engineer Interested In Developing Smarter Software And Services
Nice, I am in groups 3 and 8! I am currently an Undergraduate Student, and I desire to develop production machine learning infrastructures, as well as go a bit more in-depth through various textbooks.
Hang in there Christopher!
Graduate Student just starting out with Machine Learning! Learning more and more about this field and preparing myself to dive into it. Wish me luck!
Good luck Scarlett!
Ask lots of questions.
How far have you gone into ML?
I think I am in the same position as you and looking for someone to develop with.
I am free to share and discuss if you are still in the ML pathway.
Thank you for the wonderful post. You always provide context in an area that is so vast that it is easy to get lost, become disillusioned and quit. Keep it up.
I bought your bundle on ML and the ebooks are great.
Thanks for your kind words and your support Paul, I really appreciate it!
Hey man! Which category would i fit into if I want to apply machine learning to stuff like poker and board games? Or maybe trying to use it in the stock market?
Which book/course/path would you recommend to such a person?
Perhaps 7 or 8.
For games, you may want to study AI rather than machine learning. See a book like
Artificial Intelligence: A Modern Approach
For machine learning, my best advice for getting started is here:
I’m in group 10
Thanks Steve, it’s great to have you here.
Thanks for all the info in this post! Helps me focus my efforts to build expertise a lot. I think I’m mostly an 8 with some 6 & 1 thrown in there as well but have been a little off track by struggling through the mathematical theory. Wondering if you know of any good online communities for #8??
Hi Shailesh, nice!
Some ideas for communities for building smart software:
To some extent this site.
The IOT guys are very interested in using time series effectively in their apps – good guys to talk to.
To a lower degree, some of the AI game devs communities are good to talk to.
It is lonely. When I was building predictive models for operational use, the best guys to talk to were subject matter experts.
I belongs to groups 5 and 7
That’s great Malak!
Thanks for your nice job.
I’m a statistician and looking for a data analyst position. So I think Groups 9 and 10 are a better fit for me.
It was really an awesome post for people who is striving to learn machine learning. But in my case, i am a last year student in instrumentation engineering and i want to do a good project in machine learning using R. So is it possible to do a good project in 2 months which will really help my cv to showcase my skills.
And Thanks a lot for what you are writing, because it really helped to know it in deeper way.
These resources will help you get started with machine learning in R:
Here are some interesting project ideas for a short project:
I hope that helps.
Thanx for your support Jason.
I’m here to help if I can!
I belong to the 3rd category. It has been very challenging its definitely worth it.
Thanks Precious, it’s great to have you here!
I feel like I’m all over the place! I’m a developer-turned-manager responsible for everything related to databases at my workplace. I still like to program though. So I think I’m a 1 since I think we could use machine learning to do some predictions based on our data but I’m definitely a 6 and 7 as well. Have a lot to learn but that will be part of the challenge!
Hang in there Richard!
I very much relate to your experience. Feels like drinking out of a firehose. I would say I’m a 1, 6, 7 as well.
Thank you Jason for your informative and extremely helpful emails.
Take it slow, pick one area, one tool, one problem type. Slowly develop a portfolio to build confidence.
There’s no rush, applied machine learning is a long-term pursuit.
A very informative post. Many thanks.
I think I am a 5, 6 , 7. I am only beginning to understand the ML general overview. I have successfully installed Python and Anaconda set of tools, and tested Ok using a long code I copied and pasted. Results look great as expected.
Now I think it’s time to learn syntax I suppose ? The word CONFUSION is a great friend sometimes as you try to learn syntax
Sorry, I don’t have much on Python syntax. This might help as a start:
8) Engineer Interested In Developing Smarter Software And Services
Very nice William!
It is very useful jason. I am in the group 9.
I fall into Engineering Tribe and I am in the group 8.
Very nice Ramesh!
Hi Jason, The way you explain things and the order is simply awesome. I fall into Group 6 “Programmer Interested in Implementing Algorithms”
Very nice, take a look at this:
I have really liked all your articles about machine learning. This one is one of the best though. Really makes my interests more clear. Although, I am still undecided which of these categories I belong to. I am still an undergraduate student but I am greatly interested in learning more in detail about machine learning and applying it in the future in the field of artificial intelligence and hopefully one day try to develop new AI softwares to help the world simplying their tasks. Can you tell me which category you would classify that interest as. Also, I would love it if you could guide me in how to go about learning and developing machine learning skills. I have so far only done some basic java programming but nothing to do with machine learning yet.
I would suggest focusing on learning how to work through problems and deliver a result.
My best advice is here:
Blog is very helpful and i guess i’m in 8 🙂
I had a really hard time fitting myself into any one of these groups:
I’m a professional software engineer, but my goals for machine learning as VERY far from my day job.
I love statistics, numbers, and deriving information from data, but I don’t have a math degree and wouldn’t dare calling myself a Data Analyst.
I want to build systems, but the application to build around doesn’t exist yet. The artificial intelligence aspect is the main in most of those designs.
Here’s my goal: machine learning and data analysis for AIs for robots and chat bots.
Also, learning “without the math” doesn’t appeal to me. It’s great if something works, but being incompetent without a tool or library feels like a bad idea to me.
Sorry for the long comment
Perhaps ML Mastery is not the best place for you?
any resources for building AI / ML powered robots Jason ? I feel 8) Engineer Interested In Developing Smarter Software And Services will fit for robotics. What do you say ?
Sorry, I don’t have advice about robots. Perhaps start with small table top examples?
Before reading this blog… I had done a bit of research and searched for a text book to get started into ML. First textbook I started with had too much of maths for me (me already being 5 years into my programming career). I was not very satisfied with the book or the approach it had taken. Then I stumbled across the book “Machine Learning in Action” (mentioned above). It proved quite good since it seems to be a book written for seasoned programmers rather than students. I am happy to continue on this path. But my question is this… Even though I have been programming for more than 10 years this is my first time interaction with Python…
So i was wondering do I go back and learn Python completely before attempting ML?
No need, you can learn machine learning with your preferred programming language.
I focus on Python and R on my blog because they are popular.
Most of the production ML I have built runs in FORTRAN and Java.
Very nice blog! Just curious why there is no girl in the photo? 🙂
No idea, it was a random creative commons photo. I do not mean to offend in any way at all.
I am in group 3. Hoping to learn something interesting and creating something cool while doing my UG.
Thanks Saugat, it’s great to have you here.
I am in 3,4,8 groups
Machine Learning Researcher Interested in Impacting the Field
Very nice Gagan!
t know exactly my tribe, may be "Business Person with a General Interest") im a trader on NYSE, i want to automate my strategy with ML and i hope your interesting blog wiil help me) (i`m not developer of course)
Appreciate this. Give clarity and focus for those who are about to start the “journey”.
Thanks, I’m glad to hear that.
This is a great practical guide.
I thought there might be also classification based on applications that can overlay on top of your guide.
For example, chatbot for eCommerce is a single purpose development but it involves the currently evolving research in end-to-end neural network, that generally would be best worked by new or recent PhD’s interested in research. This is true with machine vision for self-driving cars that utilizes complex neural networks.
Sure, I like it.
Jason – I enjoy your blog-posts, and this one is awesome. Thanks for the matching resources (well thought out). I am in Tribe 2 and 8. I guess in today’s world, one has to straddle categories. Thanks and keep up the good work.
I feel like I am in group 6 an well as group 10.
Can these two groups go hand in hand?
I read your post, and thought about the tribe that I’d be most comfortable in. Unfortunately, I haven’t been able to decide where I belong. I do wish to pursue ML, but I never thought that ML will be such a big umbrella. Honestly, I’m a bit overwhelmed.
I need some time. I’m hoping that you can recommend some general, non-specific, ML books that I can get started with and then study about a topic that catches my eye, in detail. Are there any texts/resources that every ML student must read? If so, then I’d be grateful if you could tell me about them. At least this way, I’d get into the learning part, without allotting way too much time to just picking out resources.
Start small and figure it out along the way, like the rest of life.
I am a software tester, so as per my understanding i will not belong to any tribe. but i want to learn ML. so how do i start?
I am also a software tester. Follow Jason Arbon from test.ai. I started on this area on this blog post from LinkedIn: https://www.linkedin.com/pulse/links-ai-curious-jason-arbon/
Thanks for sharing.
I am in group 3
Group 9. Many hours of frustration-meandering-wallowing. Your work is like a well-rested bright clear morning. Simple complete succession of English statements containing the ideas is the most difficult to find.
If I understand the idea, I can figure out the implementation.
Instead practitioners are tying to learn themselves with incomplete explanations and academicians are ardently explaining in absence of any context.
Once self-identified, where does one find tribe-centric material, conversations, best practices?
Hats off compadre!
Well, most of the material out there is for academics and researchers.
There are some practitioner type material like this blog and some O’Reilly type books.
My proposal is that once you know what you want/where you fit, that you can use that as a filter to help choose what material will get you closer to your goal.
Does that help Billy?
Amazing post!! This is probably what I was looking for to give my endeavors the correct direction…I belong to the second tribe, and it’s great to know that I’m not alone!
Thanks Rohan. You are not alone!
I am in group 3&4
I am from Engineer “Interested In Developing Smarter Software And Services”
I was wondering how much Data Structures and Algorithms do I need to know if I mainly want to focus on the Machine Learning or Deep Learning aspect of personal software projects.
Say, if I want to build a Django website that uses ML algorithms to function.
I have gone through lots of Machine Learning content, but never came across any DSA
A deeper understanding of algorithms and data structures will help you better understand how algorithms work and how to use them more effectively, but it is not required when getting started.
You do not need to be a mechanic to dive a car.
I am a systems administrator trying to make a career shift to Machine Learning. But, I don’t fit into any of the tribes that you have listed. I have no prior experience in programming but i have started learning Python on my own. I think I want to belong to tribe 8 (Engineer Interested In Developing Smarter Software And Services) which requires lot of ground work.
But like you have mentioned in your posts, I will take a leap and see where this goes.
BTW, Your posts are awesome.
Hang in there.
This might be a good place for you to start:
Thank you so much for the methodical segregation of tribes.
Am Narendra. Currently am a computer engineer with little algorithm and data structures background, presently working as a software tester, my long term aspiration is to understand machine learning and be working in the field of machine learning (in another 1 or 2 years).
Will i be a better fit in tribe 6 or tribe 3 to get started ?
I would recommend starting where you feel most comfortable.
I definitely fall into the 5/9 category. I have ended up in small companies mostly with their thoughts of:
(1) get data
(2) do machine learning
without any real business goals other than profit. I’ve hopped away from that start-up mentality and am in a more mature company though still in more of a research style role though often with well defined business objectives.
I often use ideas in your blog as i navigate the ML/DL environment
Thanks Chad. Hang in there!
I am interested in the Academic Tribe but I can’t afford the books.
Does Someone has some electronic books to send?
You can access my best free material here:
Thanks for giving such a nice categorization!
I belong to Tribe 8.
Very nice Amitabh!
I belong to engineering tribe
6) Programmer Interested in Implementing Algorithms
Hi Jason, this article was enlightening, thank you! I’m studying Data Science and as I’m looking for positions in this field I encounter some confusion with the terminologies being used. As I’m in entry level, in this field, the ones that I find it more confusing are those where in the job description you see that there is not much infrastructure for the work of the data science its more like, ” We have data, come and find important insights”. However, for machine learning engineer positions its better established challenges. As I used to work with Organizational Network Analysis its clear to me the gap between IT and Business Units in some corporations where IT is treated more like a support role, than strategic. I would like to here your thought on that and with you have any tips on how to be more assertive in the job search. Best to you!
Sorry, I don’t have good general advice for job searching.
Generally, for entry-level roles, I see that if you can turn up with a strong portfolio of completed projects (showing you know how to work through problems end to end on your own), that this is more variable than showing you have completed MOOC courses and such.
I have some advice here on the topic:
I can associate closely with group (8), my inhibitions are however programming prowess and I probably need to work on becoming a better programmer. I do think I have an end-to-end vision and would like to learn to apply ML to industry problems in telecommunications or connected devices or such. As of now I dont have a clear picture of where and how ML can be applied.
I am able to connect myself with 3rd, 6th & 8th tribe.
6 and 7, aiming to reach 8 at some point.
6 and 7 because I’m an engineer and I want to know how to code algorithms but not so deeply, I’d be more interested in making predictions. I want to be in 8th group after becoming better in 7, because as you said logically the 8th comes from 6 and 7.
I think I fall into Engineering tribe (7 and 8) but looking forward to get into Data Tribe 9 .
This is great stuff Jason. This and previous post on “Why Get Into Machine Learning?” has started opening my mind about some things I have been probably missing. Particularly around letting people know about my knowledge and skills into this field and expertise I can offer.
I see myself strongly in Data Tribes. Primarily into group 9 “Data Scientist interested in getting better answers to business questions” with good overlap in group 10 “Data analyst interested in better explaining data” too.
I also see myself inclined to a group 4 “Machine Learning Researcher Interested in Impacting the field”
Thanks, glad to hear it!
I’m in group 8! This is a really good article, Jason. Thank you very much for your time and dedication. Your blog is awesome!
Off topic: I enjoy looking at Gartner’s Hype charts and Magic Quadrants, and use them in my writing. About Magic Quadrant, I find it difficult to interpret which block a company should be. That is, which block is good or bad. To me, all blocks look good. For example, Revolution Analytics is in Niche Players, which seems pretty good to me. However, it is not in Challengers. Won’t a niche player challenging the status quo. Similarly, Microsoft is in the Visionary quadrant but not a leader. They seem synonymous to me.
I am in group 8, 9 and 10. Wonder how can I find the relevant communities, forums etc.?
Separately, where would you put Kaggle-lers?
Here are some ideas:
Going to join tribe 8 as “machine learning engineer” sound great. 🙂
Thank you for your blog!
I belong to the category of Engineering Tribe. My interest is an intersection of 6,7,8 categories.
The Best Article for ML Beginners. Categorization of Machine Learning Tribes is very useful and informative.
Thanks. Glad to hear it.
What is the role of Quality Analyst in Machine learning platform? Is it a good idea to take Machine learning as next step in career being a QA?
I don’t know. Good question.
Business and Data groups. I will start with learning the basics of Phyton and R (and a bit of SQL), and will take it from there. Also, need to finish all the steps in your email tutorials. Btw, those are great. Thank you!
Hang in there!
i used to take tribe a 8 in “machine learning”
I’m in groups 6, 7, and 8.
Jason: I belong to tribe 1,2 or 9,10. as I am interested in understanding what business problems can machine learning solve, specific to retail (FMCG) or Healthcare industries.
I’m a student in undergraduate class but I don’t have machine learning as my subject now. ML is my own interest apart of my college syllabus I’m working on ML which I feel facinated about
Great! Hang in there.
Thank you so much for putting this out!
Great analysis. Know your student and/or customer is the first step to teaching or business success. I would just add that there is often a difference between NLP and quantitative data that may make or break finding a tribe. Working on similar datasets seems critical to the experience and ability to give tips to others.
I’m in Group 3.
Fantastic Mr Jason you’re my inspiration to learn machine learning. Efficiently described everything. keep up the work. Thank You 🙂
Nice, well done!
I am in Group 3, who is determined to self-teaching ML with a weak Math background and interested to go to the Groups 4 & 8. Thanks for doing this great blog, Dr Brownlee.
Hang in there!
Yes, I am. Thank you 🙂
I fall in Data tribes..
As usual great analysis (categorization, right?) on the different tribes. Since I have an intense SWE background I would probably be a 6 or 8.
Please keep up the good work! It’s evident you’ve spent quite a bit of effort in your tutorials and blogs, and they are making a big difference for me.
I am a software engineer, working on my ways to provide software solution in the finance field. I think I will definitely belong to either 6th or 8th tribe. Your blog is one of the best ways to learn machine learning for people of having full-time jobs without getting overwhelmed by theoretical knowledge…Thanks a lot…Keep it up.
Hang in there!
I would like to implement the algorithms with programming. So i am on 6th tribe. Thanks Jason for classification.
I want to do research in the field of AI. I have math and statistics background but not many ML application experience. Should I go straight to the papers and journals or should I try practicing more first?
It depends on your goals Leo.
If you want to add value in business, focus on working through predictive modeling problems and delivering a result.
My interest is to enter tribe 4 Machine Learning Researcher Interested in Impacting the Field
This is so great. This classification helped me to focus on my intrest only. This is highly recommended.
I’m glad it helped.
I’m in the academics group.
I think I belong to 4 and 5, as I’m an undergraduate instrested in learning Machine learning.
I’m in group 4 and 5, but with 10 years stopped in this line of research.
I belongs to Engineering Tribe
Between 5 and “I believe this tool might be useful for future research aims”
I belong to group 3
Woah, great post. I’m surely belong to group 6 and also little of 8 🙂
Your post is very usefull for me, I’m mechatronics engenear, I want to make about robot so I think that I’m belong to group 6, right?
I want to make robot auto find the fast road to goal, If I only read the books belong to group 6, can I make that robot?
Sorry, I don’t know about robots.
I belong to group 6 and 8.
Want to get into the 8th
Thanks for the lovely blog. It really gave me a good overall picture.
I’m a software engineer with 8+ years of experience, but got fascinated by Machine Learning/Data Science very recently. I feel like I fall into group 6, but will be happy if you confirm my choice. I’d be glad to get your assistance on how to go about achieving my goals.
Perhaps start here:
Amazing classification. Came across ML through some friends, with 15 years of experience in linux, I belong to group 8. Where should i start if i were to use Python?
It is important to focus on the features of the software/service and to treat the ml project as a sub-project, not the main project. The difficutly is because the ml project is ill-posed it is essentially endless. You need hard deadlines.
You can this process to get the best “good enough” model within time constraints:
Here are tutorials on how to use this process in scikit-learn:
Thank you very much for this amazing blog, I love your work a lot. I am an electronics engineering student and I want to learn ML to make some solutions. Could you please tell me my tribe.
Perhaps pick a tribe that best aligns with your goals.
This Really Helped Me In Deciding My Tribe.
Machine Learning Student in an Undergraduate or Graduate Class
I’m happy it helped!
Great Great Great Plog!
I just want to ask, Why didn’t you include those who are interested in the Artistic and creative applications of machine learning ?
Good question. I guess I’m not familiar with the artistic/creative use of algorithms, sorry.
Are you familiar with that side? How does it work exactly?
Hello Jason, thank you indeed for this very educating and enlightening post. It has cleared a thick fog about my career path in machine learning. I definitely belong to Tribe 7, aspiring to Tribe 9. I am deeply interested in using machine learning techniques and approaches to generate powerful insights that give businesses a superior competitive edge in the market place. That’s my key motivation for becoming a machine learning practitioner. Your blog has been a veritable companion on this journey. Keep up the good work!
Thanks, I’m glad it helped.
I am more close to tribe 8, however I am in pursuit of applying ML or Predictive Analysis in software testing (not web app testing). Any specific pointers that can illuminate my path?
Perhaps seek out papers on the topic and get an idea what about the state of the art.
Group 5 for me!
I am in tribe 6 and 8.
i am android and ios Developer . and interested in ML .
Thanks for sharing!
I’m 8 or 10. Excellent Jason.
Very nice, thanks!
I think I’m 6 or 8. I haven’t dabbled in programming since highschool and it’s been coming back up at my current work that it is something I want to pursue. I just don’t know where to start. I have python but can’t think of where to get started or how to for that matter.
Start small, experiment, see what you like – what interests you.
Perhaps try this tutorial:
I fit in 6, have tried tensorflow a little, did some courses also, but the courses didn’t get me excited to continue
Thanks Mr. Jason, for providing such good articles.
I believe that I fit in both 6 and 8. I’m going for “Machine Learning in Action” and “Building Machine Learning Systems with Python”.
I’m already a programmer and need to expand my knowledge. I tried learning AI before but like what you said in your other article, I got overwhelmed with a lot of information (math, algorithms, languages…) and left the course behind.
But trying to get my hands dirty again and this time, just top-down approach and what I need.
https://bit.ly/2MqmRCD – MIT online course for business people – Tribe 1
5) General Researcher Interested in Modeling Their Problem is one area that I fit
Also, I am interested on testing AI systems. For example, how to test ASR, NLU and TTS systems that are based on AI.
Thank you for the excellent resources you have created. I am surprised that google did not direct me to you earlier .(I came across you when I was searching for power analysis introductions.)
I have Masters in Physics and Bachelors in Electrical engineering. I have worked on verification for very short amount of time, and I did not enjoy it. Due to few pesonal issues I have been out of workforce for last couple of years. I have started machine learning journey because of its potential, work availability and because it excites me !
I would fall in following order-
9. Data Analytics + Data explanation and novel exploration & intelligence.Images,sound,natural phenomenon, or any wide variety of data about which would teach me new things about world.
( I know tall order ! but since you have created such wonderful and detailed resource, you deserve a detailed answer from someone you are trying to help)
10. Data Science + Business- Have to make money and make lives of people better !
11. General Researcher – On last position because its not in current plan, but definitely in future !
Again, Warmest thanks for your efforts!
Thanks, and welcome to the ML Mastery community!
Hey! Can you help me finding someone from group 8
This is a common question that I answer here:
I would like to work on improving search engines and recommendation systems.
That sounds like a fun area.
I’m in none of these tribes. I’m just a high school graduate willing to get into the maze of machine learning without gettting lost.
Excellent categorization (tribes).
I fall in the Engineering Tribe, specifically in 6 and 8. More of 8.
The content is written in a very good manner. It’s looking like I am in a classroom.
I think I fall in
2) Manager interested in delivering a project; and
6) Programmer interested in implementing the algorithm
Hey Jason !
Really appreciate your work.
I am a Mechanical Engineer working in a manufacturing firm. I have no prior experience in machine learning but i do have problems which i think would be solved using ML.
What tribe do i belong to ?
General Researcher ??
Perhaps one of the “Engineering Tribes”.
i think i’m in 6 or 8 tribe.
I am in 5
Is it okay if I just start machine learning just for hobbysake ??but I have some interest in the group 1
Yes, a great way to start!
I do not think that I fit into any of the tribes that you listed. I have been trained as a hardware, sensors and signal processing engineer and I would like to pivot into the machine learning direction. I have experience writing code at the very low level (embedded C for microcontrollers) and the high level (matlab for developing algorithms and signal processing coefficients) but I don’t consider myself to be a software developer or programmer. What advice would you give me in choosing a path to get bring machine learning into my toolset?
The tribes are more focused on how you would like to use the techniques.
You may be interested in using ml in software for example.
I belong to “8) Engineer Interested In Developing Smarter Software And Services”.
Thanks, and welcome!
Great article. Explains clearly where to focus on. Greats Kudos
Thanks. I’m glad it helped.
This is Excellent.Perfect for me in making decisions on which tribes to follow and attend their events.Thank you so much.
Tanks, I’m glad it helped.
Please help! I am just starting in programming and machine learning.
My goals are:
1)make a Starcraft2 bot with neural networks.
2)make a trading bot with AI
3)make a bot that will automatically make protein foldings on fold.it using ML.
4)get to a point where I can analyze brain signals using my Brainwave headset or other and get ideas of the results for developing models with ML.
What tribe(s) should I choose?
Thank you very much for your articles! I’m willing to develop a strong ML, developing and analytical mindset with the intuition into this skills.
Best Regards to you and your work!!!
p.s.: right now I’m taking a neural networks course, but the problem is that I don’t know how to implement them outside the class. Making bots, using API’s and implementing that ANN’s is still a big mistery.
I don’t think the machine learning tribes above are relevant for you. I think you might be better off with a site/material focused on AI instead of ML.
The most efficient path for me to take to ML Mastery is probably thru tribes 9 & 10 since I have 30+ years experience as a data professional. But I’m inclined to think more like a 5. My problem of choice is to understand the two-way relationship between the ML modeling and data modeling. For example, how does each influence the other, and what scope of knowledge is needed to understand the association, if in fact it even exists.
Thanks for your guidance.
Hmm, terminology is hard.
I think you might be talking about descriptive modeling (what happened) and predictive modeling (what will happen).
They both can use the same data prep and modeling techniques, although toward different ends, and therefore different methods of evaluation.
Machine Learning Student in a Undergraduate or Graduate Class
I belong to Academic tribe. In group 3/4. Currently working on a project related to medical diagnosis using chest X-ray
great articles. I belong to 1/2/6 tribes. what suggestions do you have for me?
For 6, this will help:
I think I am in group 3 and 8! Thanks for this awesome guide 🙂
MAN, your site is awesome!! Best one i found so far! So structured and consistent with tones of useful information. Thanks Jason, i almost lost my believe that i can cope with it, but you brought me back a hope.
Thanks man, keep it up!!!
I am groups number 1,2, 7 and 8 btw.
Hang in there.
I am the same guy who enjoyed your explanation , and commented in below thread
Could you please help me find to match my tribe .
A brief introduction about me , I am having 9+years of experience in PL-SQL Application development in India. I always get fascinated with latest and emerging technologies . Due to raising need of more money in today’s world for a luxurious life , we always try to get updated with demanding technologies, So that we could add more Indian Rupees/Pounds/Dollars in our salary , that’s why opted to devote myself in this stream where not every other person want to dive .
Hope you are getting my point , please define my tribe . Thanks in advance for your time.
Perhaps read about the above groups and select one that you think best describes you?
I thought I belong to 8, but after read most of the comments I believe 9 could be fine too. Cool articles you have in your blog btw! =)
I am working as software engineer so I think I belong to group 7 and 8. However, I am currently learning data science and data analysis (group 9 and 10). Do you think I can have a mix between these groups?
Yes, a mix is good.
I belong to the data tribe (9&10). ML has been really overwhelming for me. Here you are really narrowing down so that one can digest it bit by bit.
This is giving back to society. No one can pay you for this.
Thanks for keeping the site active and updated.
Very well-written and informative article Jason.
I am a Mechanical Engineer by day, and a Data Scientist and Machine Learning enthusiast by night. Would you put me in group 8?
I am taking online courses and trying to add to my knowledge by reading insightful articles such as this one. Do you have any specific advice for my journey to become a ML practitioner?
Great, many thanks, Jason.
I belong to tribe 5. I am using ML to classify my cancer data. I tried SVM and NB.
I want to have probability prediction not only class prediction to predict also heterogeneous samples. I am new comer and still couldn’t figure out how should I do it. Should I go with fuzzy classification?
I really appreciate if you give me some hint.
In scikit-learn you can call model.predict_proba() to predict probabilities:
Machine Learning Student in Graduate Class
Sir recently i read a article .It says something radical .Someone might be interested to read it and it adds value to community.could yu publish this in blog .
Thanks for sharing. I don’t really follow AI.
I belong to academic and engineering tribes.
I’m coming into this as a hobbyist and not necessarily looking to get employment. I’m exploring how I can use datasets to get better answers for my other interests like trading and fantasy sports.
What tribe would I fall into?
8) Interested In Developing Smarter Software And Services
Finally, i feel someone understood my frustration… I simply want to understand machine learning to a level that i can apply it to my own dataset and problem…
Thank you for taking the time to explain the “Tribes”
You’re very welcome, I’m happy it helped!
Great article. Thank you.
Data Product Owners/Managers – which tribe do they belong to?
Good question, perhaps business or engineering tribes?
I’m interested on “8) Engineer Interested In Developing Smarter Software And Services”
Great classification, very useful, I think in some companies are giving wrong tasks to some profiles, especially, between data and engineering profiles.
I m interested in 3 and 4..kindly help me
Great, start here:
Great posting Jason! Re-connecting.
Am interested in machine learning for stock market trading, i belong to group 9
Thanks for the great post,
I just returned back to your site after a long time (I might have the excuses that you described in the other article).
I read this article and found myself interested in tribe 8 (Machine Learning Engineer) but I have a lack of knowledge in ML. So I went with tribe 6 because I found the suggested books good. I want to read them.
Should I start https://machinelearningmastery.com/process-for-working-through-machine-learning-problems/ after finishing those books?
Yes. Perhaps in parallel.
Thanks for great explanation.
What the best tribe matches our path?
What the best learning plan, and resources ?
(Please, read sentences below)
We’re computer engineering students of the last year, want to develop a speaker recognition system as our graduation project.
The application and its challenges are slightly clear for us, in addition, we have some prerequisites of audio signal-related background.
But we have no prior experience in ML.
BTW, the goal is to implement a more accurate production system starting from what latest researches and experiments had resulted.
So, we may adopt a certain method/approach/solution trying to enhance it, or developing a hybrid model, that combines the only strength points of other existing model.
I recommend starting here:
I’m # 1…..I think. I’m a biochemist with an MBA and I’m looking to leverage machine learning and “data science” in general to make data-driven business decisions. I’m interested in using my new skills in a new role or a familiar role that values DS/ML and provides me a competitive advantage.
As an SEO, I am interested in fields somewhere between data science tribes and web developers (engineering) tribes. Also, one-off modelling is super useful even if not reliable model, apply machine learning can help identify issues faster. Thanks for that Jason
Thanks for sharing!
Amazing Jason ! Thanks for clarifying that. It is true that knowing what to learn and defining precise learning goals is a true challenge. What would advice on how to build a killer learning plan that we be confident it is flexible to make absolutely future-proof in the areas that we desire? Thanks!
Good question, see this:
I am in group 10 with a desire to be a part of group 9. I have to say that this is the first time I feel like machine learning is presented in a digestible way for someone like me who has no formal training and has spent much more time implementing code and software to process and understand data. Thanks for creating this incredible resource, Jason!
I am group 6 but my goal is to become group 9 or 10.
I am a Mechanical / Automotive Engineer, managing teams of people using data analytics to develop racing cars. I reckon I am tribes 2, 8 & 10.
I have gone through some of your articles and I am convinced you are a prophet in the machine learning and programming field. Thank you for being a great light.
My question is can you recommend a blog, or article with the same depth, structure, and insight as yours in other fields of programming like web development.
I feel I belong in the engineering Tribe, —-having a wide interest in subjects and delivering project category.
Thanks for your kind words!
No, sorry. I don’t know about other similar blogs.
I love your blog and appreciate your process of explanation.
I don’t think I belong to any of the described tribes.
Not a Business tribe: I have general interest but I’ve already started trying. Also not a Manager delivering projects.
Not in the Academic tribe: I went to school for Architecture, my program didn’t stress
Not in the Data Tribe: I’d say I’m mentally closest to data professionals because I love to be able to develop insights and use them to create predictions. But I’ve never worked as a Data Scientist or Analyst ever.
I’m a former Visual Effects Artist (Film and TV) who’s looking to change/pivot his career into Machine Learning.
Is there a tribe for a Design/Art professional who enjoys the process of iterating and re-iterating?
The prototypical nature of ML is what I enjoy the most. There’s no right answer and even if there is, in production it will change due to new data and/or the model losing its efficiency. There are so many parallels to between Design Thinking and ML.
While I’m directly not in any of the tribes above, I feel like I relate a little to each of them. As someone with his hand on the pulse of the ML world: do hear from Designers/Artists coming into this world? (It feels like an extremely lonely world out there to be an analytically minded artist)
I absolutely enjoy your website and the resources you continue to provide. I recommended it to my mum, who is trying to learn to code and possibly get into ML. Thanks for doing this!!
The tribes are just a general guide, perhaps you can devise a new tribe that is a good fit for you.
Jason, I am a newbie to ML, just finished the course on DS, and yet have so many questions left while trying to do my first project on Kaggle. I am absolutely in love with your blog! You answer any question I may have as I am trying to progress through my research. Your kind guidance as well as the resources you have suggested in this post are invaluable. Thank you!
And I belong to the mixed group too.
You’re very welcome!
I am a mechanical engineering who is keen on ML
Actually, it seems I don’t fit in any tribe!!
I am in the healthcare sector. Before the pandemic hit last year, we were interested in doing a ML project related to reducing patient stay in the hospital. But I am looking to change into Healthcare Informatics. Would that make me a member of tribe 1 or an aspiring member of tribe 10?
Perhaps both. It’s just a guide to help you think through the different ways you can contribute.
Where does someone who wants to learn about A.I becoming self aware go?
A.I. is a much broader topic. What do you consider as A.I. here?
I am a mechanical engineer got to know about machine learning a while ago and since then wanted to learn it. What tribe do you think I would come under?
Thank you Jason for this interesting blog.
I belong to tribes 7 and 9.
Interesting post, I think I’m in tribe 8.
It looks like this post was written–and the recommendations made–in around 2015. Do you consider they are still the best options for each tribe, or are there newer books that would be better?
Hi Wayne…I believe this post is still very much relevant.
Thank you indeed, I am definitely in tribe 3 and have long term goal of becoming tribe 4.
Thank you for the feedback Sara!
Tribe 8! I came across your website to implement ensemble techniques and I liked your posts! Now, I want to go through all the posts you have on your website from the start and learn!
Thank you for the feedback and support Bhavya!
I’m confused in 3, 6 and 8. It’s been 1 month I have been into ML. How can I get a more clear idea about my tribe?
Hi SURAJ…Please clarify some of your goals with machine learning so that we may better assist you.
hello, here how can I join a tribe? 3 to be specific
Hi Tasmia…Of the tribe descriptions provided in the tutorial, which environments seem most appealing to your learning style?
Aside from your ML expertise, you are an awesome teacher Jason! I really appreciate this website and the learning methods you espouse are really helpful for learning not just ML, but any other technical topic.
Thank you Naman for your feedback and support! We greatly appreciate it!
I am in Data Scientist group in Data Tribe.
Thank you for your feedback Rinku! We wish you the best on your machine learning journey!
What an amazing…crisp … To the point article. No useless gyaan or fancy words. Awesome piece worth bookmarking.
Thank you Komal for your feedback and support! We greatly appreciate it!
Written in 2015, do you think that this article needs an update?
Hi Omer…The content is still very relavent today.
target group 5
now in 3
How to join the group if I am interested to join?