This GitHub repository gathers the most popular cheatsheets and quick reference guides for Artificial Intelligence (AI) and Machine learning (ML).
For an ease of download and browse over the files, a Google Drive version of this GitHub repository is available here.
The global structure of this GitHub repository follows to some extent the following AI and Machine Learning roadmap.
- 01- Mathematics
- 02- C++
- 03- Python
- 04- Computer architecture
- 05- Data structures
- 06- Automata theory
- 06- Complexity theory
- 07- SQL
- 08- Data cleaning
- 09- Data visualization
- 10- Mathematical logic
- 11- Introduction to AI
- 12- Machine learning
- 13- Deep learning
- 14- Metrics to evaluate ML algorithms
- 15- Reinforcement learning
- 16- Time series
- 17- Git
- 01- Mathematics
- Calculus cheat sheet all reduced
- Calculus cheat sheet
- Linear Algebra in 4 pages
- Probability cheat sheet
- Probability distribution cheat sheet
- Statistics cheat sheet
- Super-cheatsheet-mathematics
- Summary statistics
- 02- C++
- C++ Reference Card
- C++ Libraries
- C++ OOP Reference Card
- 03- Python
- Python for Beginners
- Python Reference Cheatsheet
- Python cheatsheet
- Python for Data Science cheatsheet
- Numpy cheatsheet
- Pandas cheatsheet 1
- Pandas cheatsheet 2
- Matplotlib cheatsheet 1
- Matplotlib cheatsheet 2
- Scikit-Learn cheatsheet
- List, Tuples, Sets, Dictionary
- Tutorial Python
- 04- Computer architecture
- Computer organisation cheatsheet
- 05- Data structures
- Classification of Data structures
- Data structures
- Complexity
- Resources
- 06- Automata theory
- Languages and Automata cheathseet
- Automata cheatsheet
- Context-Free Grammar cheatsheet
- 06- Complexity theory
- Complexity Theory Cheat Sheet
- Computability Theory Cheat Sheet
- 07- SQL
- SQL-quick-guide
- SQL operations
- SQL query execution order
- SQL commands
- SQL-basics-cheat-sheet-a4
- SQL joins-cheat-sheet-a4
- Study-guide-data-retrieval-with-SQL
- SQL Roadmap
- 08- Data cleaning
- Data-cleaning-checklist
- Data-cleaning-guide
- Data-preparation-cheatsheet
- Feature engineering
- Feature-selection-methods
- Hypothesis-testing-cheatsheet
- 09- Data visualization
- Core principles of Data Visualization
- Visual Vocabulary
- Data visualization cheatsheet
- The chart chooser
- From Data to Visualization
- 10- Mathematical logic
- cheatsheet-logic-models
- 11- Introduction to AI
- cheatsheet-states-models
- cheatsheet-variables-models
- 12- Machine learning
- Machine learning process
- Machine-learning-map
- Machine learning algorithms
- How to choose a ML algorithm 1
- How to choose a ML algorithm 2
- Time complexity of ML algorithms
- Comparison of ML algorithms 1
- Comparison of ML algorithms 2
- Comparison of ML algorithms 3
- Comparison of ML algorithms 4
- Comparison of ML algorithms 5
- super-cheatsheet-machine-learning
- Machine learning cheatsheets
- Machine learning explainability
- Machine learning operations MLOps
- 13- Deep learning
- super-cheatsheet-deep-learning
- Large Language Models cheatsheet
- main types of neural networks
- Architecture - Classification MLP
- Architecture - Regression MLP
- Activation Function - Hidden Layer
- Activation Function - Output Layer
- Activation Functions
- 14- Metrics to evaluate ML algorithms
- Metrics-machine-learning
- Performance-measure-machine-learning
- 15- Reinforcement learning
- Reinforcement learning cheatsheet 1
- Reinforcement learning cheatsheet 2
- 16- Time series
- Time-series-cheat-sheet
- 17- Git
- Git-cheat-sheet
- Git-cheat-sheet 2