Last Updated on June 7, 2016 This is a guest post by Kevin Dalias. I recently had the chance to attend Strata 2014 in Santa Clara, and since it was my first time at the conference, I tried to attend as many sessions as I could to understand what really makes data science tick these days. And of course, I heard plenty of the usual “a data scientist must be…” bullet points, but session after session, a new addition to the […]

Last Updated on August 16, 2020 This post is a spotlight interview with Jhonatan de Souza Oliveira on the topic of Bayesian Networks. Could you please introduce yourself? My name is Jhonatan Oliveira and I am an undergraduate student in Electrical Engineering at the Federal University of Vicosa, Brazil. I have been interested in Artificial Intelligence since the beginning of college, when had my first adventure investigating and building a simple chatbot for a Symposium website. I also am a member of an […]

Last Updated on June 7, 2016 I came across an upcoming book that might interest you. It is titled Bootstrapping Machine Learning by Louis Dorard, PhD. A 40-page sample is provided and I enjoyed it. I think the final book will be a valuable read. Cover of the upcoming book: Bootstrapping Machine Learning Louis takes the position that machine learning is commoditized to the point where if you are an application developer, you don’t need to learn machine learn ing algorithms, you only need to learn machine […]

Last Updated on June 7, 2016 What is the difference between a Data Analyst and a Data Scientist and what type of work do they do all day? These questions and questions like them are answered in the new free ebook The Data Analytics Handbook: Data Analysts and Data Scientists. Cover of the The Data Analytics Handbook: Data Analysts and Data Scientists The ebook was created by Brian Liou, Tristan Tao and Elizabeth Lin. Brian and Tristan are Computer Science + Statistics grads and run the blog statsguys. Although […]

Last Updated on August 15, 2020 In a previous blog post we looked at the ebook of interviews with data analysts and data scientists put together by Liou, Tao and Lin. In this blog post we look at the second book in the series titled The Data Analytics Handbook CEOs and Managers. The Data Analytics Handbook CEOs and Managers What are managers looking for in a Data Analyst and a Data Science position, what skills do they require and how do […]

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 […]