Colorado Reed from Metacademy wrote a great post recently titled “Level-Up Your Machine Learning” to answer the question he often receives of: What should I do if I want to get ‘better’ at machine learning, but I don’t know what I want to learn? In this post you will discover a summary of Colorado recommendations […]
Julia Evans wrote a post recently titled “Machine learning isn’t Kaggle competitions“. It was an interesting post because it pointed out an important truth. If you want to solve business problems using machine learning, doing well at Kaggle competitions is not a good indicator of that skills. The rationale is that the work required to […]
David Mimno is an assistant professor in the Information Sciences department at Cornell University. He has a background and interest in Natural Language Processing (NLP), specifically topic modeling. Notably, he is the chief maintainer of MALLET, the Java-based NLP library. I recently came across a blog post by David titled “Advice for students of machine […]
I get a lot of emails asking about how I got interested in machine learning and about my background. I don’t think my story is special or interesting, but I’m happy to share it and honored I’m asked. This post feels a little self-indulgent. I figure it can be the definitive version of my story […]
A question I get asked a lot is: How can I make money with machine learning? You can get a job with your machine learning skills as a machine learning engineer, data analyst or data scientist. That is the goal of a great many people that contact me. There are also other options. In this […]
It is difficult to stay motivated when self-studying machine learning. The standard test datasets can be quite obtuse and disconnected from you and from your everyday life. Boring even. A trick that you might like to use is to find and work on a dataset that matters to you. In this post, we will look at […]
Complete Small Focused Projects and Demonstrate Your Skills A portfolio is typically used by designers and artists to show examples of prior work to prospective clients and employers. Design, art and photography are examples where the work product is creative and empirical, where telling someone you can do it is not valued the same as […]
Identify and Tackle Your Self-Limiting Beliefs and Finally Make Progress I get a lot of email from developers and students looking to get started in machine learning. The first question I ask them is what is stopping them from getting started? I try to get to the heart of what they are struggling with, and almost […]
In this post I lay out a concrete self-study roadmap for applied machine learning that you can use to orient yourself and figure out your next step. I think a lot about frameworks and systematic approaches (as evidenced on my blog). I would consider this post a vast expansion of my previous thoughts on a self-study […]
Reading bootstrapping machine learning, Louis mentioned a paper that I had to go off and read. The title of the paper is Machine Learning that Matters (PDF) by Kiri Wagstaff from JPL and was published in 2012. Kiri’s thesis is that the machine learning research community has lost its way. She suggests that much of machine […]
