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 […]
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. […]
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. What are managers looking for in a Data Analyst and […]
If you get serious with data analysis and machine learning in python then you will make good use of IPython notebooks. In this post we will review some takeaway points made by Fernando Perez, the creator of IPython in a keynote presentation at SciPy 2013. The title of the talk was IPython: from the shell to […]
This is a guest post by Igor Shvartser, a clever young student I have been coaching. This post is part 3 in a 3 part series on modeling the famous Pima Indians Diabetes dataset that will investigate improvements to the classification accuracy and present final results (update: download from here). In Part 1 we defined the problem […]
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 […]
This is a guest post by Igor Shvartser, a clever young student I have been coaching. This post is part 2 in a 3 part series on modeling the famous Pima Indians Diabetes dataset (update: download from here). In Part 1 we defined the problem and looked at the dataset, describing observations from the patterns we […]
This is a guest post by Igor Shvartser, a clever young student I have been coaching. This post is part 1 in a 3 part series on modeling the famous Pima Indians Diabetes dataset that will introduce the problem and the data. Part 2 will investigate feature selection and spot checking algorithms and Part 3 in […]
A Top-Down Strategy for Beginners to Start and Practice Machine Learning. Getting started is much easier than you think. In this post I show you the top-down approach for getting started in applied machine learning. You will discover the four steps to this approach. They should feel familiar because it’s probably the same top-down approach […]
Need Help Getting Started with Applied Machine Learning? These are the Step-by-Step Guides that You’ve Been Looking For! What do you want help with? The most common question I’m asked is: “how do I get started?” My best advice for getting started in machine learning is broken down into a 5-step process: Step 1: Adjust Mindset. […]
