This video covers the basics of working with probability distributions in Python, including the uniform, normal, binomial, geometric, exponential and Poisson distributions. It also includes a discussion of random number generation and setting the random seed.

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This is lesson 22 of a 30-part introduction to the Python programming language for data analysis and predictive modeling. Link to the code notebook below:

Python for Data Analysis: Probability Distributions
https://www.kaggle.com/hamelg/python-for-data-22-Probability-Distributions


This guide does not assume any prior exposure to Python, programming or data science. It is intended for beginners with an interest in data science and those who might know other programming languages and would like to learn Python.

I will create the videos for this guide such that you should be able to learn a lot just watching on YouTube, but to get the most out of the guide, it is recommended that you create a Kaggle account so that you can copy and edit each lesson so that you can follow along and run code yourself.

Introduction to Python Playlist:
https://www.youtube.com/playlist?list=PLiC1doDIe9rCYWmH9wIEYEXXaJ4KAi3jc

Link to the Python for Data Analysis written guide index page:
https://www.kaggle.com/hamelg/python-for-data-analysis-index .


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