How to Get Started With Recommender Systems

Recommender systems may be the most common type of predictive model that the average person may encounter. They provide the basis for recommendations on services such as Amazon, Spotify, and Youtube. Recommender systems are a huge daunting topic if you’re just getting started. There is a myriad of data preparation techniques, algorithms, and model evaluation methods. Not all of the techniques will be relevant, and in fact, the state-of-the-art can be ignored for now as you will likely get very […]

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Best Machine Learning Resources for Getting Started

Last Updated on August 16, 2020 This was a really hard post to write because I want it to be really valuable. I sat down with a blank page and asked the really hard question of what are the very best libraries, courses, papers and books I would recommend to an absolute beginner in the field of Machine Learning. I really agonized over what to include and what to exclude. I had to work hard to put myself in the […]

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Hands on Big Data by Peter Norvig

Last Updated on August 16, 2020 When I’m asked about resources for big data, I typically recommend people watch Peter Norvig’s Big Data tech talk to Facebook Engineering from 2009. It’s fantastic because he’s a great communicator and clearly and presents the deceptively simple thesis of big data in this video. In this blog post I summarize this video for you into cliff notes you can review. Essentially, all models are wrong, but some are useful. Quote by George Box. […]

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6 Practical Books for Beginning Machine Learning

Last Updated on August 16, 2020 There are a lot of good books on machine learning, but most people buy the wrong ones. A question I get asked the most is what books should people buy to get stared in machine learning. My answer to beginners is: “don’t buy textbooks“. In this post I want to point out a few key books that are aimed at beginners that you should buy (and read!) if you are just starting out. I […]

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How to get the most from Machine Learning Books and Courses

Last Updated on September 29, 2016 There are a lot of machine learning books and courses available and a trend towards free university courses and ebooks. With so much excellent resources available it can feel overwhelming. So much so that it may prevent you from getting started or making progress. In this post I want to share with you my tips for self study that allow me to touch a resource once, extract everything I think I can learn from […]

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5 Steps to Thinking Like a Designer in Machine Learning

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 […]

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Introduction to Bayesian Networks with Jhonatan de Souza Oliveira

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 […]

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Bootstrapping Machine Learning: An Upcoming Book on Prediction APIs

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 […]

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The Data Analytics Handbook: Data Analysts and Data Scientists

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 […]

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The Data Analytics Handbook: CEOs and Managers

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 […]

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