This book is of dynamic nature and the one who want to go in this field, have a good option of Learning Python. this book has many examples and has an approach which is practical through which new and advanced topics are explained which are introductory. it starts with the basics of programming and python and then explores several topics like GUIs, web applications and data science. Through this book, you can easily create an application which is fully fledged.
If you already have knowledge of math and programming with Python, you are halfway into the development and processing. For teaching these complex topics, most of the books are started with theories but digital signal processing in python introduces techniques by showing you how they are applied in the real world.
Think Bayes: Bayesian Statistics Made Simple is an introduction to Bayesian statistics using computational methods. This book uses Python code instead of math, and discrete approximations instead of continuous mathematics. As a result, what would be integral in a math book becomes a summation, and most operations on probability distributions are simple loops.
What you need to know about Python: The absolute essentials you need to get Python up and running is designed to act as a brief, practical introduction to Python. It is full of practical examples which will get you up and running quickly with the core tasks of Python. It assumes that you know a bit about what Python is, what it does, and why you want to use it.