This is a great series. In this edition, pay special attention to the sections on BigML and Weka.

The Official Blog of

This is the second in a series of blog posts comparing BigML with other machine learning services. As you may recall from the first post in the series, I am primarily evaluating cloud-based services aimed at making machine learning accessible to non-experts like myself. Having previously introduced the competition and the criteria for comparison, let’s now see what it takes to get started and load your data into each service.

Think of a machine learning dataset as a simple table of data. Each row is an example that you want to learn from (e.g., the sales data for a particular wine), and each column describes a property of the data (e.g., the sales price of the wine). Your data may be stored in an Excel spreadsheet, a database, or perhaps even in a plain CSV (Comma-Separate Values) file. To begin learning from your data, you must properly format it…

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Two More Coursera Courses Start Today

Coursera has so many courses, it is difficult to keep track. New ones are starting all the time. Here are 2 more that will be beneficial to people interested in learning more about data science.

  • Statistics One – Technically, it started yesterday, but you will not miss out on much if you start today. If you are lacking some skills in statistics, this is probably a great place to start.
  • Intro to Computational Finance and Financial Econometrics – If you are interested in data science and finance, or if you want to know if you are interested in data science and finance, it is worth checking out this course.

Happy Studying Again!