The Course is a Sphinx project made of : Jupyter notebooks */*.ipynb files. Python files using sphinx-gallery */*.py files. ReStructuredText or Markdown files. All notebooks and python files are ...

Welcome to the Machine Learning Tutorials repository! This collection of Jupyter notebooks is designed to help you get started with machine learning using Python and Scikit-Learn. Whether you're a ...

A/B testing machine learning models can pose some challenges that need to be addressed. These include dealing with noisy or incomplete data, accounting for confounding factors and interactions ...

In this article, you will learn how to test for normality in Machine Learning data using three common methods: graphical, numerical, and statistical. Selected by the community from 33 contributions.

This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments. What you ...

This book is for data scientists and ML engineers who are working with Python and want to further boost their ML model’s performance by using the appropriate hyperparameter tuning method. Although a ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

They also compared these values to those that would have resulted from randomized lab testing policies. For each test and reward component, the policy generated by the machine learning algorithm would ...