AI-ML-cheatsheets

This GitHub repository gathers the most popular cheatsheets and quick reference guides for Artificial Intelligence (AI) and Machine learning (ML).

Google Drive

For an ease of download and browse over the files, a Google Drive version of this GitHub repository is available here.

AI-ML-roadmap

The global structure of this GitHub repository follows to some extent the following AI and Machine Learning roadmap.

The structure of the folder

• 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
  

The content of the folder

• 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