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Discussion on: DATA SCIENCE vs MACHINE LEARNING

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Matt Curcio

If you are interested, look into 'Exploratory Data Analysis' to start. As the name suggest, it is the first step in looking at your data. It usually consists of boxplots(think: std. dev. and outliers), histograms (distributions, data spread and outliers) and then some houskeeping (what is your data comprised of {categorical, nominal, numerical or continuous} or {character, list, etc}, data types.

I like Roger Peng, leanpub.com/exdata. Free, and easy intro but it is more R than Python but you can get the main ideas easily.

For the next step after that let me know and I can suggest more...