Python Data Science Handbook: Essential Tools for Working with Data 1st Edition

Not as easy or straightforward as "Python for Data Analysis " but because it uses Jupyter it's easy on the eyes to read. Highly recommend going to Staples or Office Max and getting the book spiral bound.

When I first received this book, I was surprised that it didn't get to scikit-learn until the last third of the book. The first third is about numpy and pandas, and the middle third is about matplotlib. Now that I've been applying it at work, however, I've found that the items covered in the first two thirds were really essential. I wouldn't be nearly as productive if I had just jumped straight to the sections on scikit-learn. The author does an excellent job covering broad terrain with enough detail that you are able to apply it to your problems. You will find yourself going back to use this book as a reference.

I am currently taking a Machine Learning course from Udacity and this book has proven to be a great reference guide for several projects and quizes. Although it does not go in depth in regards to machine learning (although almost half of the book is dedicated to it), it does give an understanding of essential concepts. For those interested in machine learning I would recommend bying "Hands-On Machine Learning with Scikit-Learn and TensorFlow" by Geron as well as this book.There is no one book for data science, and this one is no exception. Just keep that in mind before buying it.Other than that, I am really happy with my purchase.P.S. For those complaining about black and white graphs and diagrams - check the author's GitHub.

I have used R for a few years and this was my first book that covered Python for data science. Even though it does not go into super great depth in any area, it is definitely a super book. It covers everything from Pandas, Matplotlib, and scikit-learn. I would highly recommend it for anyone that is new to Python and/or data science. The book is written with Jupyter Notebooks so it is easy to follow along and try code from the book in your own notebook.

I've just finished this book. The author gives a well-written introduction into Machine-Learning with Python Scikit-Learn and illustrates each chapter with well-designed examples that are easy to follow and understand. I am very pleased with this book and can definitely recommend to everyone who is a beginner in the field and wants to quickly get hold on the practical approaches to ML.

This is by far the best book out in market to get you started with using python for data science. You will need some basic understanding of python and machine learning to understand concepts here, but this book will definitely take you skill to next level.This is no-nonsense book and goes deep into stuff which are relevant and important to do data science in python, every page is rich in information and provides practical use case, optimization tricks and adds new dimensions to your understanding of topic.

The book is just great - amazing combination of details and brevity. I had programming experience but no experience with Python at all before I started reading this book. Very good fit for my qualification. Recommended for everyone who is going to start a new way into Data Science using Python.

This is an excellent reference book for people working with data science. Remember, 80% of the effort in machine learning, data analysis or data science in general is about processing data and understanding data. This book is for that purpose and I think it's the best book out there about data processing, analysis and visualization using python. If you look for hardcore machine learning, go for other books. Highly recommended!