Python: From None to Machine Learning
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Agenda

  • 1. Agenda

Agenda

  • 1.1. Python: Basics
  • 1.2. Python: Intermediate (level 1)
  • 1.3. Python: Intermediate (level 2)
  • 1.4. Python: Advanced
  • 1.5. Python: Design Patterns
  • 1.6. Python: Test Driven Development
  • 1.7. Python: DevOps, CI/CD
  • 1.8. Python: Performance Optimization
  • 1.9. Python: Data Science and Analysis
  • 1.10. Python: Numpy
  • 1.11. Python: Pandas
  • 1.12. Python: Microservices
  • 1.13. Python: Django
  • 1.14. Python: FastAPI
  • 1.15. Python: Flask
  • 1.16. Python: Graphical User Interface

Install

  • 1. Install
  • 2. Install Python
  • 3. Install Git
  • 4. Install Github
  • 5. Install IDE
  • 6. Install Project
  • 7. Install Doctest

Python Basics

  • 1. About
  • 2. Syntax
  • 3. Types
  • 4. Iterables
  • 5. Unpack
  • 6. Mappings
  • 7. Conditional
  • 8. Loops
  • 9. Comprehensions
  • 10. Files
  • 11. Functions
  • 12. Exception
  • 13. Object Oriented Programming
  • 14. Recap

Python Intermediate

  • 1. About
  • 2. Unpack
  • 3. Idiom
  • 4. Enum
  • 5. Match
  • 6. Type Annotation
  • 7. Dataclass
  • 8. JSON
  • 9. CSV
  • 10. Regular Expressions
  • 11. Datetime and Timezones
  • 12. Operator
  • 13. Modules and Packages
  • 14. Logging
  • 15. Mathematics
  • 16. Tests

Python Advanced

  • 1. About
  • 2. Syntax
  • 3. Generators
  • 4. Functional Programming
  • 5. Decorators
  • 6. Object Oriented Programming
  • 7. Protocols
  • 8. Performance
  • 9. Concurrency
  • 10. Recap

Database

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

Design Patterns

  • 1. About
  • 2. UML
  • 3. Idiom
  • 4. Type Annotation
  • 5. Dataclass
  • 6. Operator
  • 7. Object Oriented Programming
  • 8. Protocols
  • 9. Decorators
  • 10. Behavioral
  • 11. Structural
  • 12. Creational
  • 13. Practices
  • 14. Paradigms

Numpy

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

Pandas

  • 1. About
  • 2. Import & Export
  • 3. Series
  • 4. DataFrame
  • 5. Date
  • 6. Recap
  • 7. Case Studies

Matplotlib

  • 1. About
  • 2. Figure
  • 3. Style
  • 4. Chart
  • 5. Advanced
  • 6. Recap

Stdlib

  • 1. Modules and Packages
  • 2. Mathematics
  • 3. Locale
  • 4. Pickle
  • 5. XML
  • 6. Operating System
  • 7. Builtin
  • 8. Loop
  • 9. Performance
  • 10. TKInter

DevOps

  • 1. About
  • 2. Good Engineering Practices
  • 3. Tests
  • 4. Debugging
  • 5. Type Annotation
  • 6. CI/CD

Network

  • 1. About
  • 2. Protocols
  • 3. Web
  • 4. Transport

HTTP and Microservices

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

Django

  • 1. About
  • 2. Conf
  • 3. Models
  • 4. Admin
  • 5. Orm
  • 6. Views
  • 7. Utils
  • 8. API
  • 9. DevOps
  • 10. Async

FastAPI

  • 1. About
  • 2. FastAPI
  • 3. Pydantic
  • 4. Database
  • 5. Auth
  • 6. DevOps
  • 7. Use Cases
  • 8. Appendix

Data Science

  • 1. About
    • 1.1. Description
    • 1.2. Program
    • 1.3. Agenda
    • 1.4. Certificate
    • 1.5. Survey
  • 2. Jupyter
    • 2.1. Jupyter
  • 3. Python
    • 3.1. Python Syntax
    • 3.2. Types
    • 3.3. Sequences
    • 3.4. Mappings
    • 3.5. Conditionals
    • 3.6. Looping
    • 3.7. Control Flow
    • 3.8. Functions
    • 3.9. Object Oriented Programming
    • 3.10. Packages
    • 3.11. Math
    • 3.12. Serialization
    • 3.13. Performance
  • 4. Data Visualization
    • 4.1. Plotly
    • 4.2. Bokeh
    • 4.3. Seaborn
    • 4.4. Generowanie grafów
  • 5. Scipy
    • 5.1. SciPy

Machine Learning

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

Object Oriented Programming

  • 1. Paradigm
  • 2. Python
  • 3. Dynamic Typing

Blogposts

  • 1. Machine Learning Introduction

Dragon

  • 1. Dragon v1.0
  • 2. Dragon v2.0
  • 3. Dragon v3.0
  • 4. ADR Template
  • 5. Dragon ADR Init Name
  • 6. Dragon ADR Init Position
  • 7. Dragon ADR Position Set
  • 8. Dragon ADR Position Change
  • 9. Dragon ADR Damage Make
  • 10. Dragon ADR Damage Take
  • Writing Progress
  • References in the Book
  • Survey
  • Python History
  • 14.3. Further reading
Python: From None to Machine Learning
  • Docs »
  • 1. About
  • Edit on GitHub

1. About¶

About

  • 1.1. Description
  • 1.2. Program
  • 1.3. Agenda
  • 1.4. Certificate
  • 1.5. Survey

2. Jupyter¶

Jupyter

  • 2.1. Jupyter

3. Python¶

Introduction

  • 3.1. Python Syntax
  • 3.2. Types
  • 3.3. Sequences
  • 3.4. Mappings
  • 3.5. Conditionals
  • 3.6. Looping
  • 3.7. Control Flow
  • 3.8. Functions
  • 3.9. Object Oriented Programming
  • 3.10. Packages
  • 3.11. Math
  • 3.12. Serialization
  • 3.13. Performance

4. Data Visualization¶

Data Visualization

  • 4.1. Plotly
  • 4.2. Bokeh
  • 4.3. Seaborn
  • 4.4. Generowanie grafów

5. Scipy¶

Scipy

  • 5.1. SciPy
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© Copyright 2023, CC-BY-SA-4.0, Matt Harasymczuk <matt@astrotech.io>, last update: 2023-03-24 Revision 8155e8f5.

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