Python: From None to Machine Learning
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  • License
  • Python Versions
  • References in the Book
  • Survey
  • Python History
  • Further reading

Agenda

  • Python: Basics
  • Python: Intermediate (level 1)
  • Python: Intermediate (level 2)
  • Python: Advanced
  • Python: Design Patterns
  • Python: Test Driven Development
  • Python: DevOps, CI/CD
  • Python: Performance Optimization
  • Python: Data Science and Analysis
  • Python: Numpy
  • Python: Pandas
  • Python: Microservices
  • Python: Django
  • Python: FastAPI
  • Python: Flask
  • 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

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. OOP

Intermediate

  • 1. About
  • 2. Star
  • 3. Match
  • 4. Idiom
  • 5. Generators
  • 6. JSON
  • 7. CSV
  • 8. TOML
  • 9. Pickle
  • 10. Regex
  • 11. Datetime
  • 12. Enum
  • 13. Modules
  • 14. Logging
  • 15. Math
  • 16. Tests

Advanced

  • 1. About
  • 2. Syntax
  • 3. Typing
  • 4. Dataclass
  • 5. OOP
  • 6. Operator
  • 7. Protocol
  • 8. Functional
  • 9. Decorators
  • 10. Performance
  • 11. Multiprocessing
  • 12. Threading
  • 13. AsyncIO

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. OOP
  • 4. Protocols
  • 5. Decorators
  • 6. Behavioral
  • 7. Structural
  • 8. Creational
  • 9. Practices
  • 10. Paradigms

Numpy

  • 1. About
    • 1.1. Numpy
    • 1.2. Numpy Configuration
    • 1.3. Precision
    • 1.4. Built-ins
    • 1.5. Performance
  • 2. Create
    • 2.1. Array Create
    • 2.2. Array Range
    • 2.3. Array Generate
    • 2.4. Array Create Recap
    • 2.5. Array Serialize
    • 2.6. Array Import
    • 2.7. Array Export
  • 3. Attributes
    • 3.1. Array Data Types
    • 3.2. Array Shape
    • 3.3. Array Attributes
    • 3.4. Array Attributes
  • 4. Indexing
    • 4.1. Array Getitem
    • 4.2. Array Slice
    • 4.3. Array Axis
    • 4.4. Array New Axis
    • 4.5. Array Logic
    • 4.6. Array Select
    • 4.7. Advanced Indexing
  • 5. Methods
    • 5.1. Array Round
    • 5.2. Array Sort
    • 5.3. Array Methods
    • 5.4. Array Concatenation
  • 6. Random
    • 6.1. Random Generator
    • 6.2. Random Values
    • 6.3. Random Distributions
    • 6.4. Random Draw
  • 7. Operations
    • 7.1. Array Iteration
    • 7.2. Array Arithmetic
    • 7.3. Array Broadcasting
  • 8. Statistics
    • 8.1. Array Reduction
    • 8.2. Statistics
  • 9. Math
    • 9.1. Trigonometry
    • 9.2. Linear Algebra
  • 10. Polynomial
    • 10.1. Polynomials

Pandas

  • 1. About
  • 2. Migrations
  • 3. Series
  • 4. DataFrame
  • 5. Date
  • 6. Recap
  • 7. Case Study

Matplotlib

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

Stdlib

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

DevOps

  • 1. About
  • 2. Quality
  • 3. Tests
  • 4. Debugging
  • 5. CI/CD

Network

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

Microservices

  • 1. About
  • 2. 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. Case Study

Data Science

  • 1. About
  • 2. Jupyter
  • 3. Python
  • 4. Visualization
  • 5. 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
  • 13. Articles

OOP

  • 1. Paradigm
  • 2. Python

Dragon

  • 1. Dragon
  • 2. ADR
Python: From None to Machine Learning
  • 1. About
  • Edit on GitHub

1. About¶

About

  • 1.1. Numpy
  • 1.2. Numpy Configuration
  • 1.3. Precision
  • 1.4. Built-ins
  • 1.5. Performance

2. Create¶

Create

  • 2.1. Array Create
  • 2.2. Array Range
  • 2.3. Array Generate
  • 2.4. Array Create Recap
  • 2.5. Array Serialize
  • 2.6. Array Import
  • 2.7. Array Export

3. Attributes¶

Attributes

  • 3.1. Array Data Types
  • 3.2. Array Shape
  • 3.3. Array Attributes
  • 3.4. Array Attributes

4. Indexing¶

Indexing

  • 4.1. Array Getitem
  • 4.2. Array Slice
  • 4.3. Array Axis
  • 4.4. Array New Axis
  • 4.5. Array Logic
  • 4.6. Array Select
  • 4.7. Advanced Indexing

5. Methods¶

Methods

  • 5.1. Array Round
  • 5.2. Array Sort
  • 5.3. Array Methods
  • 5.4. Array Concatenation

6. Random¶

Random

  • 6.1. Random Generator
  • 6.2. Random Values
  • 6.3. Random Distributions
  • 6.4. Random Draw

7. Operations¶

Operations

  • 7.1. Array Iteration
  • 7.2. Array Arithmetic
  • 7.3. Array Broadcasting

8. Statistics¶

Statistics

  • 8.1. Array Reduction
  • 8.2. Statistics

9. Math¶

Math

  • 9.1. Trigonometry
  • 9.2. Linear Algebra

10. Polynomial¶

Polynomial

  • 10.1. Polynomials
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© Copyright 2023, CC-BY-SA-4.0, Matt Harasymczuk <matt@astronaut.center>, last update: 2023-05-29. Revision 32a8e8ba.

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