wtf is cheatsheets-ai?

This repository is a collection of reference cheat sheets for machine learning and deep learning practitioners. Cheat sheets are single-page visual summaries of the most commonly used commands, functions, and concepts for a particular tool, designed to be kept handy while working rather than reading full documentation from scratch. The collection covers the core Python libraries used in data science and machine learning work: Tensorflow and Keras for building neural networks, Numpy and Scipy for numerical computing, Pandas for working with tabular data, Scikit-learn for traditional machine learning algorithms, Matplotlib and Seaborn for creating charts and visualizations, and ggplot2 for R users. It also includes cheat sheets for PySpark (a tool for processing large datasets across multiple machines), Dask (a library for parallel computing in Python), and R Studio's dplyr and tidyr packages for data wrangling. For those new to neural networks, there are also visual reference sheets showing the "Neural Networks Zoo" (a diagram of different neural network architectures), neural network cells, and neural network graphs. All sheets are available individually or as a single combined PDF download. The repository is MIT licensed.