Python - from None to AI
  • License
  • Install
  • Python Versions
  • Python History
  • Links
  • References

Basics

  • 1. About
  • 2. Syntax
  • 3. Numeric
  • 4. Logic
  • 5. Strings
  • 6. Iterables
  • 7. Mappings
  • 8. Nested
  • 9. Unpack
  • 10. Conditional
  • 11. While
  • 12. For
  • 13. Comprehensions
  • 14. Files
  • 15. Functions
  • 16. Exceptions
  • 17. OOP
  • 18. Modules
  • 19. Recap

Intermediate

  • 1. About
  • 2. Syntax
  • 3. Star
  • 4. Enum
  • 5. Match
  • 6. Encoding
  • 7. Regex
  • 8. Datetime
  • 9. Idiom
  • 10. Iterator
  • 11. OOP
  • 12. Serialization
  • 13. Pickle
  • 14. TOML
  • 15. CSV
  • 16. JSON
  • 17. Pathlib
  • 18. Logging
  • 19. Modules
  • 20. Recap

Advanced

  • 1. About
  • 2. Syntax
  • 3. Typing
  • 4. OOP Dataclass
  • 5. OOP Paradigm
  • 6. OOP Inheritance
  • 7. OOP Abstract
  • 8. OOP Metaprogramming
  • 9. OOP Accessors
  • 10. OOP Operator
  • 11. FP Paradigm
  • 12. FP Apply
  • 13. FP Patterns
  • 14. Generators
  • 15. Async Paradigm
  • 16. Async AsyncIO

Performance

  • 1. About
  • 2. Introduction
  • 3. Optimization
  • 4. Profiling
  • 5. Case Study
  • 6. Threading
  • 7. Multiprocessing
  • 8. Extensions

Testing

  • 1. About
  • 2. Random
  • 3. Syntax
  • 4. Doctest
  • 5. Unittest
  • 6. Recap

CI/CD

  • 1. DevTools
  • 2. Distribute
  • 3. Lint
  • 4. Quality
  • 5. Security
  • 6. Webdev

DevOps

  • 1. About
  • 2. Quality
  • 3. Tests
  • 4. Debugging

Database

  • 1. About
  • 2. Theory
  • 3. ORM
  • 4. Normalization
  • 5. NoSQL
  • 6. SQL
  • 7. SQLite3
  • 8. SQLAlchemy
  • 9. Case Study

Design Patterns

  • 1. About
  • 2. UML
  • 3. Decorators
  • 4. Creational
  • 5. Behavioral
  • 6. Structural

Numpy

  • 1. About
  • 2. Array
  • 3. Attributes
  • 4. Random
  • 5. Indexing
  • 6. Operations
  • 7. Methods
  • 8. Statistics
  • 9. Math
  • 10. Polynomial

Pandas

  • 1. About
  • 2. Read
  • 3. To
  • 4. Series
  • 5. DataFrame
  • 6. Date
  • 7. Case Study

Matplotlib

  • 1. About
  • 2. Figure
  • 3. Style
  • 4. Chart
  • 5. Case Study

Stdlib

  • 1. Modules
  • 2. Collections
  • 3. Math
  • 4. Locale
  • 5. XML
  • 6. Operating System
  • 7. String
  • 8. Builtin
  • 9. Type
  • 10. Loop
  • 11. TkInter

Network

  • 1. About
  • 2. Protocol
  • 3. Web
  • 4. Transport
  • 5. Case Study

Microservices

  • 1. About
  • 2. HTTP
  • 3. Microservices
  • 4. Auth

Django

  • 1. About
  • 2. Setup
  • 3. Settings
  • 4. Models
  • 5. Admin
  • 6. ORM
  • 7. Views
  • 8. Templates
  • 9. Templatetags
  • 10. Forms
  • 11. Manage
  • 12. Locale
  • 13. Middleware
  • 14. Utils
  • 15. Auth
  • 16. API
  • 17. Ninja
  • 18. Tests
  • 19. Apps
  • 20. Deploy

FastAPI

  • 1. About
  • 2. FastAPI
  • 3. Pydantic
  • 4. Database
  • 5. Auth
  • 6. DevOps
  • 7. Case Study

Data Science

  • 1. About
  • 2. Jupyter
  • 3. Python
  • 4. Visualization
  • 5. Scipy
  • 6. Geopandas

Machine Learning

  • 1. About
    • 1.1. About Certificate
    • 1.2. About Description
    • 1.3. About Survey
  • 2. Introduction
    • 2.1. What is Data?
    • 2.2. Basic Statistics
    • 2.3. Machine Learning Introduction
    • 2.4. Glossary
    • 2.5. Datasets
    • 2.6. Machine Learning Algorithms
    • 2.7. Features
    • 2.8. Classifiers
  • 3. Sklearn
    • 3.1. scikit-learn
  • 4. Model Quality
    • 4.1. Model Quality
    • 4.2. Principal Component Analysis
  • 5. Decision Trees
    • 5.1. Decision Tree
  • 6. Regressions
    • 6.1. Linear Regression
    • 6.2. Logistic Regression
  • 7. K-Nearest Neighbors
    • 7.1. K Nearest Neighbors
  • 8. Bayes
    • 8.1. Naive Bayes
  • 9. Support Vector Machines
    • 9.1. Support Vector Machines
  • 10. Clustering
    • 10.1. K-Means Clustering
  • 11. Neural Networks
    • 11.1. Deep Neural Network
    • 11.2. Convolutional Neural Network
  • 12. References
    • 12.1. References
  • 13. Articles
    • 13.1. Machine Learning Introduction
    • 13.2. Notes

Artificial Intelligence

  • 1. About

OOP

  • 1. Paradigm
  • 2. Python

Dragon

  • 1. English
  • 2. Polish
  • 3. ADR
Python - from None to AI
  • 1. About

1. About

About

  • 1.1. About Certificate
  • 1.2. About Description
  • 1.3. About Survey

2. Introduction

Introduction

  • 2.1. What is Data?
  • 2.2. Basic Statistics
  • 2.3. Machine Learning Introduction
  • 2.4. Glossary
  • 2.5. Datasets
  • 2.6. Machine Learning Algorithms
  • 2.7. Features
  • 2.8. Classifiers

3. Sklearn

Sklearn

  • 3.1. scikit-learn

4. Model Quality

Model Quality

  • 4.1. Model Quality
  • 4.2. Principal Component Analysis

5. Decision Trees

Decision Trees

  • 5.1. Decision Tree

6. Regressions

Regressions

  • 6.1. Linear Regression
  • 6.2. Logistic Regression

7. K-Nearest Neighbors

K-Nearest Neighbors

  • 7.1. K Nearest Neighbors

8. Bayes

Bayes

  • 8.1. Naive Bayes

9. Support Vector Machines

Support Vector Machines

  • 9.1. Support Vector Machines

10. Clustering

Clustering

  • 10.1. K-Means Clustering

11. Neural Networks

Neural Networks

  • 11.1. Deep Neural Network
  • 11.2. Convolutional Neural Network

12. References

References

  • 12.1. References

13. Articles

Articles

  • 13.1. Machine Learning Introduction
  • 13.2. Notes
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© Copyright 2025, Matt Harasymczuk <matt@python3.info>, last update: 2025-07-11.