#machine learning Cheatsheets

A concise cheat sheet for the scikit-learn library, covering essential functionalities for machine learning in Python. This guide includes key concepts, model selection, preprocessing techniques, and evaluation metrics with practical examples.

A comprehensive cheat sheet covering essential concepts, tools, and techniques in Data Science. It provides a quick reference for machine learning algorithms, data manipulation, statistical methods, and more.

A comprehensive cheat sheet covering fundamental machine learning concepts, algorithms, and techniques. Useful for quick reference and understanding key aspects of machine learning workflows.

A comprehensive cheat sheet covering essential Artificial Intelligence concepts, algorithms, and techniques. This guide is designed to provide a quick reference for AI practitioners and students.

A comprehensive cheat sheet for PyTorch, covering essential concepts, modules, and functions for building and training neural networks.

A concise cheat sheet for Keras, covering fundamental concepts, common layers, model building, training, and evaluation techniques for deep learning.

A quick reference guide to TensorFlow, covering its core concepts, common operations, and essential functions for building and training machine learning models.