blog/content/reviews/books/python-data-science-essentials-learn-the-fundamentals-of-data-science-with-python.md

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title = "Python Data Science Essentials - Learn the fundamentals of Data Science with Python - Alberto Boschetti"
date = 2016-12-16

[taxonomies]
tags = ["books", "alberto boschetti", "reviews", "python", "data science",
"it", "2 stars"]
+++

[GoodReads Summary](https://www.goodreads.com/book/show/25527772-python-data-science-essentials---learn-the-fundamentals-of-data-science):
Key Features Quickly get familiar with data science using Python Save time -
and effort - with all the essential tools explained Create effective data
science projects and avoid common pitfalls with the help of examples and hints
dictated by experience Book Description

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{{ stars(stars=2) }}

It's hard to explain this book, mostly because it's hard to get to whom it is
targeted.

Is it targeted to people that already know Machine Learning and want to learn
Python? No, the book goes into lengths into some algorithms and has "easy to
write, but not quite right" code to do so.

Is it targeted to people that know Python but want to learn Machine Learning?
No; even if some algorithms are explained in length, some aren't and there is
very little "you use this when you have data like that" explanations.
Actually, there is very little explanation on where an algorithm should be
used.

Is it targeted to people that don't know Python and don't know Machine
Learning and want to learn but? This is the gray area of the book: Again, the
code is pretty simple and does not follow Python coding standards and the ML
part is really shallow on the "when" and "why" sections.

In the end, the book is simply an extended version of Scikit-Learn manual --
and I even have doubts if the manual isn't better because it explains when an
algorithm should be used.