Essential Cheat Sheets for Machine Learning and Deep Learning Researchers

For beginners, entering machine learning and deep learning can be challenging, and deep learning libraries are often hard to grasp. To address this, the author created a GitHub repository of cheat sheets to assist learners and invites contributions.

Project URL: kailashahirwar/cheatsheets-ai

1. Keras

Keras is a powerful and easy‑to‑use deep‑learning library; when combined with Theano or TensorFlow it provides high‑level neural‑network APIs for developing and evaluating models. This cheat sheet is useful for Python data science and machine‑learning tasks.

2. NumPy

NumPy is the core library for scientific computing in Python, offering high‑performance multi‑dimensional array objects and tools for array operations. This cheat sheet supports Python data‑science and machine‑learning workflows.

3. Pandas

This Pandas cheat sheet focuses on data wrangling. Built on NumPy, Pandas provides easy‑to‑use data structures and analysis tools for Python, making it valuable for data science and machine‑learning projects.

4. SciPy

SciPy is one of the core packages for scientific computing, offering mathematical algorithms and convenience functions built on NumPy, including linear‑algebra utilities. This cheat sheet aids Python data‑science and machine‑learning tasks.

5. Matplotlib

Matplotlib is a Python 2D plotting library that generates publication‑quality figures in various hard‑copy formats and interactive environments. This cheat sheet is intended for Python data‑science visualisation.

6. Scikit-learn

Scikit-learn is an open‑source Python library that provides a unified interface for a wide range of machine‑learning, preprocessing, cross‑validation, and visualisation algorithms. This cheat sheet supports Python data‑science and machine‑learning projects.

7. Neural Networks Zoo

This cheat sheet covers almost all types of neural networks, providing a quick reference for researchers.

8. ggplot2

ggplot2 follows a grammar of graphics, allowing users to build any plot using a dataset, a set of geometric objects, and a coordinate system. This cheat sheet is useful for data visualisation.

Source: Medium (original article) and Zhihu translation. © The original author retains copyright; the content is reproduced with attribution.