Are you trying to learn Python from scratch? It helps to learn from books that have boss status. That’s just what’s up. Nobody wants to waste time on confusing books or books that require searching a lot online to fill in the gaps.
These books are awesome because they will provide you with a solid foundation in programming to help you understand data science and machine learning better.
Python Crash Course is intended for anybody with no programming background. This book is the best programming one to start reading first in your data science journey.
This book covers all of the basics with helpful exercises to illustrate the concepts. Further, it doesn’t dive into the subject too deep, which is crucial for beginners in this subject.
Going too deep too early in the learning process can create confusion.
Introducing Python is also an introductory text on the subject and is can be understood by beginners, too.
From my own experience, this book is more easily understood after reading through a Crash Course in Python.
Big Book of Small Python Programming is the best to use after reading the previous two when you went to practice your skills to keep up with them.
Also, after reading the other two books, you will need to practice code.
This book is for those who don’t have a project and need exercises.
Fluent in Python is great to fill in the gaps that the other two books did not address. Each page is contains details on how to implement or improve code.
Keep in mind that there may be chapters which feel complicated in this book since this book takes you deeper and covers the next level in programming in Python.
Serious Python offers the required information to enhance your Python skills even further. This book discusses topics such as memorization, multithreading, a better method for creating decorators and how to deal with relational databases.