Implementing machine learning algorithms from scratch seems like a great way for a programmer to understand machine learning. And maybe it is. But there some downsides to this approach too. In this post you will discover some great resources that you can use to implement machine learning algorithms from scratch. You will also discover some of […]
How Do I Get Started In Machine Learning? I’m a developer. I have read a book or some posts on machine learning. I have watched some of the Coursera machine learning course. I still don’t know how to get started… Does this sound familiar? The most common question I’m asked by developers on my newsletter is: How do […]
You want to learn machine learning to have more opportunities at work or to get a job. You may already be working as a data scientist or machine learning engineer and looking to improve your skills. It is about as easy to pigeonhole machine learning skills as it is programming skills (you can’t). There is […]
Are you a Java programmer and looking to get started or practice machine learning? Writing programs that make use of machine learning is the best way to learn machine learning. You can write the algorithms yourself from scratch, but you can make a lot more progress if you leverage an existing open source library. In […]
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. […]
Need Help Getting Started with Applied Machine Learning? These are the Step-by-Step Guides that You’ve Been Looking For! What do you want help with? The most common question I’m asked is: “how do I get started?” My best advice for getting started in machine learning is broken down into a 5-step process: Step 1: Adjust Mindset. […]
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 […]
It is good practice to have reproducible outcomes in software projects. It might even be standard practice by now, I hope it is. You can take any developer off the street and they should be able to follow your process to check out the code base from revision control and make a build of the […]
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 […]
There are lots of things you can do to learn about machine learning. There are resources like books and courses you can follow, competitions you can enter and tools you can use. In this post I want to put some structure around these activities and suggest a loose ordering of what to tackle when in […]
