Modeling and Simulation in Python is an introduction to modeling and simulation of physical systems using the Python porting to python 3 pdf language. If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing.
While most resources start with theory to teach this complex subject, Think DSP: Digital Signal Processing in Python introduces techniques by showing you how they’re 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 an integral in a math book becomes a summation, and most operations on probability distributions are simple loops. Think Stats: Exploratory Data Analysis in Python is an introduction to Probability and Statistics for Python programmers.
It emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health.