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