Last Updated on June 18, 2019 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. Shashank Singh I moved to Mumbai, India to joined Idyllic Software and I came in contact with amazing people with such […]

Last Updated on September 27, 2016 A question I get asked a lot is: What is the best programming language for machine learning? I’ve replied to this question many times now it’s about time to explore this further in a blog post. Ultimately, the programming language you use for machine learning should consider your own requirements and predilections. No one can meaningfully address those concerns for you. No one can meaningfully address those concerns for you. What Languages Are Being Used Before […]

Last Updated on September 5, 2016 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. Machine Learning that Matters Kiri’s thesis is that the machine learning research community has lost its way. She suggests that much of machine learning is done for machine learning’s sake. She points to three key problems: Overfocus on […]

Last Updated on June 7, 2016 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 program in the post “Self-Study Guide to Machine Learning” that really hit a chord in the community. Let’s jump […]

Last Updated on December 24, 2016 Identify and Tackle Your Self-Limiting Beliefs andFinally 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 always it is a self-limiting belief that has halted their progress. In this post, I want to touch on some […]

Last Updated on September 27, 2016 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 showing them. In this post, I will convince you that building a machine learning portfolio has value to you, […]

Last Updated on September 27, 2016 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 some ideas for datasets that you could use to motivate and even accelerate your journey into applied machine learning. […]

Last Updated on September 27, 2016 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 post, I want to highlight some of those other options and try to get your gears turning. There are […]

Last Updated on June 10, 2019 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 that I can use to answer similar inquiries in the future. The lessons that I point to underly much […]

Last Updated on August 16, 2020 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 learning“. This is a great post and includes similar advice that I give to programmers and coaching students. It’s […]