Python 3: from None to Machine Learning
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Introduction

  • 1. Installing Python
  • 2. References in the book
  • 3. About Python Language
  • 4. IDE - Integrated Development Environment

Python Basics

  • 1. Entry Test
  • 2. Syntax
  • 3. Types
  • 4. Sequences
  • 5. Mappings
  • 6. Conditionals
  • 7. Looping
  • 8. Control Flow
  • 9. Functions
  • 10. Object Oriented Programming
  • 11. Exit Test

Python Intermediate

  • 1. Entry Test
  • 2. Builtins
  • 3. Looping
  • 4. Object Oriented Programming
  • 5. Modules and Packages
  • 6. Mathematics
  • 7. Datetime and Timezones
  • 8. Serialization
  • 9. Database
  • 10. Regular Expressions
  • 11. Operating System
  • 12. GUI
  • 13. Exit Test

Python Advanced

  • 1. Entry Test
  • 2. Functions
  • 3. Performance
  • 4. OOP Paradigm
  • 5. OOP Protocols
  • 6. Object Oriented Programming
  • 7. Design Patterns
  • 8. Paradigms
  • 9. Concurrency
  • 10. Exit Test

Quality and CI/CD

  • 1. Software Engineering Conventions
  • 2. The Zen of Python
  • 3. Code Smells
  • 4. ReST and Sphinx documentation
  • 5. Unit Testing
  • 6. Pytest
  • 7. Python WAT?!
  • 8. Logging
  • 9. Warnings
  • 10. Basic Debugging
  • 11. Advanced Debugging
  • 12. Introspection
  • 13. Type Annotation
  • 14. Introspection
  • 15. Type Checking
  • 16. Annotating existing code
  • 17. CI/CD

Network and HTTP

  • 1. Protocols
  • 2. Transport
  • 3. HTTP and Web
  • 4. Django

Numerical Analysis, Data Science

  • 1. Introduction
  • 2. Jupyter
  • 3. Python
  • 4. Numpy
  • 5. Pandas
  • 6. Matplotlib
  • 7. Data Visualization
  • 8. Scipy

Machine Learning

  • 1. Introduction
  • 2. Sklearn
  • 3. Model Quality
  • 4. Decision Trees
  • 5. Regressions
  • 6. K-Nearest Neighbors
  • 7. Bayes
  • 8. Support Vector Machines
  • 9. Clustering
  • 10. Neural Networks
  • 11. References

Blogposts

  • 1. Wprowadzenie do Machine Learning w Pythonie

Appendixes

  • 1. History
  • 2. Further reading
  • 3. Books
  • 4. Video
  • 5. Python 2 vs. 3
  • 6. Python Foundations
  • 7. Python Intermediate
  • 8. Python Advanced
  • 9. Python in Networking
  • 10. Django Framework
  • 11. Python in Testing
  • 12. Python in Science and Engineering
  • 13. Python in Machine Learning
  • 14. References
  • 15. Copyright
    • 15.1. MIT License
Python 3: from None to Machine Learning
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  • 15. Copyright
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15. Copyright

15.1. MIT License

Copyright (c) 2019 Matt Harasymczuk

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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© Copyright 2019, Matt Harasymczuk <[email protected]> Revision aef731b5.

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