Project layout is critical for machine learning projects just as it is for software development projects. I think of it like language. A project layout organizes thoughts and gives you context for ideas just like knowing the names for things gives you the basis for thinking. In this post I want to highlight some considerations […]
For as long as I have been participating in data mining and machine learning competitions, I have thought about automating my participation. Maybe it shows that I want to solve the problem of building the tool more than I want to solve the problem at hand. When working on a dataset, I typically spend a […]
The Python conference PyCon2014 has held recently and the videos for the conference are online. I have been working my way through the interesting machine learning ones and will share a few on this over the coming weeks. A great talk if you are starting out in data science or machine learning in python was […]
This is a project spotlight with Shashank Singh a programmer and machine learning enthusiast. Could you please introduce yourself? I did Bachelors of Technology in Computer Science. I co-founded a startup at 23, spectacularly crashed it by 26th birthday. After that I was feeling particularly low and pretty dry of inspiration for quite some time. I […]
Machine Learning has been commoditized into a service. This is a recent trend that looks like it will develop into the mainstream like commoditized storage and virtualization. It is the natural next step. In this review you will learn about BigML that provides commoditized machine learning as a service for business analysts and application integration. […]
This is a project spotlight with Artem Yankov. Could you please introduce yourself? My name is Artem Yankov, I have worked as a software engineer for Badgeville for the last 3 years. I’m using there Ruby and Scala although my prior background includes use of various languages such as: Assembly, C/C++, Python, Clojure and JS. I […]
Implementing a machine learning algorithm in code can teach you a lot about the algorithm and how it works. In this post you will learn how to be effective at implementing machine learning algorithms and how to maximize your learning from these projects. Let’s get started. Benefits of Implementing Machine Learning Algorithms You can use […]
When I’m asked about resources for big data, I typically recommend people watch Peter Norvig’s Big Data tech talk to Facebook Engineering from 2009. It’s fantastic because he’s a great communicator and clearly and presents the deceptively simple thesis of big data in this video. In this blog post I summarize this video for you […]
Machine Learning is a multidisciplinary field and it can be very confusing when you are getting started to differentiate machine learning from the closely related fields of Artificial Intelligence and Data Mining. In this post you will learn about those fields that are related to machine learning. Specifically, you will learn about the boundaries of […]
It is important to know why machine learning matters so that you know the intrinsic value of the field and of methods and open questions in the field. Like knowing your why, knowing the value of the field can be used as a powerful filter of information and help you focus on those methods that […]
