Data Science Essentials in Python

Data Science Essentials in Python

I am excited to announce the first (actually, beta) edition of my new book, "Data Science Essentials in Python. Collect → ​Organize​ → ​Explore​ → ​Predict​ → Value​," just released by the Pragmatic Bookshelf.

The book is intended for seasoned data scientists and statisticians migrating from R to Python, as well as for beginners willing to learn elements of data science in Python. (Knowledge of Python 3 at freshman/sophomore level and a descent distribution Python, such as Anaconda, are required.)

The book leads you from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset. It covers text mining, machine learning, and network analysis; processing numeric data with the NumPy and Pandas modules; and describing and analyzing data using statistical and network-theoretical methods. It has actual examples of data analysis at work, as well as mini-projects for you to enjoy. 

The book is available for purchase at the publisher's site, as well as on Amazon, Barnes & Noble, and other venues.

Dmitry, glad to see that you work in this important and fast-growing field, in which good books are still few. I'll definitely take a look as I am very much interested in this topic.

It is a great achievement to write any book!, I hope many copies are sold. Additionally it is in a very nice collection of programing books.

Sudipta, you are absolutely free not to buy it.

It's a very hard decision to pay for a book these days on topics like this. You should reconsider. You might have gone into a wrong agreement with your publishers. When Andrew Ng can offer his esteemed course on coursera for free, this book I suppose will not have the same impact. The choice is yours.

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