The First Book You Need to Succeed as an Aspiring Data Scientist

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I’m yet to find an important topic that is missing.

I have constantly advocated being language agnostic, meaning that data science is beyond the languages we use.

But Joel takes an opinionated approach, claims Python is the best language to get started. So if you are more comfortable with R, this book isn’t for you. Barring that caveat, the table of contents took me by surprise. I couldn’t find any important topic that was missing from the list.

It starts from “what is data science” and goes on to basic python, linear algebra, statistics, data visualization, probability, databases, machine learning, clustering, neural networks, networks, recommender systems, NLP, and finally, big data.

He really has covered the range of topics sufficient for a beginner without overwhelming you with unnecessary textbook theories and complicated code blocks. In Joel’s own words:

“It’s got math, but only as much as is totally necessary. It’s got scraping and cleaning and munging. It’s got machine learning. It’s got databases and MapReduce. Necessarily it doesn’t go deep into any of these, but I like to think it establishes a broad, solid foundation.”


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