Last Updated on August 15, 2020 Hal Varian is the chief economist at Google and gave a talk to Electronic Support Group at EECS Department at the University of California at Berkeley in November 2013. The talk was titled Machine Learning and Econometrics and was really focused on what lessons the machine learning can take away from the field of Econometrics. Hal started out by summarizing a recent paper of his titled “Big Data: New Tricks for Econometrics” (PDF) which […]

Last Updated on June 7, 2016 Louis Dorard has released his book titled Bootstrapping Machine Learning. It’s a book that provides a gentle introduction to the field of machine learning targeted at developers and start-ups with a focus on prediction APIs. I just finished reading this book and I want to share some my thoughts. If you are interested, I have already reviewed the sample Louis provides on his webpage that covers the first two chapters. Bootstrapping Machine Learning Overview […]

Last Updated on June 17, 2019 I recently watched a Google Tech Talk with Eric Ladizinsky who visited the Quantum AI Lab at Google to talk about his D-Wave quantum computer. The talk is called Evolving Scalable Quantum Computers and is great, I highly recommend it. I’ve had quantum computing on my mind and another tech talk went by titled Quantum Machine Learning and I had to jump on it. The talk is by Seth Lloyd from MIT. The talk […]

Last Updated on June 7, 2016 What is the difference between a Data Analyst and a Data Scientist. This question is considered from the perspective of researchers and academics in the third instalment in the series of The Data Analytics Handbook. The first book contained 7 interviews with working analysts and data scientists. The second book contained 9 interviews with CEOs and managers. This third book in the series contains 8 interviews with academics and researchers and is called The Data Analytics Handbook: Researchers and […]

Last Updated on June 7, 2016 A question that comes up from time to time is: What hardware do I need to practice machine learning? There was a time when I was a student when I was obsessed with more speed and more cores so I could run my algorithms faster and for longer. I have changed my perspective. Big hardware still matters, but only after you have considered a bunch of other factors. TRS 80!Photo by blakespot, some rights […]

Last Updated on June 7, 2016 Online communities are invaluable in machine learning, regardless of your skill level. The reason is that, like programming, you never stop learning. You simply cannot know everything, there are always new algorithms, new data and new combinations to discover and practice. Communities help. You can get your questions answered, learn by answering other peoples questions and discover new areas from reading through the exchanges. Machine learning communities have had a big impact on my […]

Last Updated on June 7, 2016 Data Origami is a new website by Cameron Davidson-Pilon that provides data science screencasts. It is a cool idea and a cool site. Cameron was kind enough to give me access to the site so that I could review it. I watched all of the videos I could and wrote up all my notes, and in this post you will get a sneak peek into Cameron’s new site Data Origami. Data Origami Logo Data […]

Last Updated on September 29, 2016 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 this post you will discover the major platforms and open source machine learning libraries you can use in Java. […]

Last Updated on June 7, 2016 There are a lot of blogs and videos on machine learning and more being created every day, week and month. If you are working or at school, it can feel overwhelming to keep up with some much material. Worse, you feel like you will be at some great disadvantage if you do miss something. In this post you will learn how subscribing to machine learning and data science newsletters can save you time and […]

Last Updated on August 15, 2020 The book Applied Predictive Modeling teaches practical machine learning theory with code examples in R. It is an excellent book and highly recommended to machine learning practitioners and users of R for machine learning. In this post you will discover the benefits of this book and how it can help you become a better machine predictive modeler. About the Book Applied Predictive Modeling is written by Max Kuhn and Kjell Johnson. Max Kuhn is […]