Python: From None to Machine Learning
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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

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. Star
  • 3. Enum
  • 4. Match
  • 5. Idiom
  • 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. Type Annotation
  • 4. Dataclass
  • 5. Operator
  • 6. Object Oriented Programming
  • 7. Protocols
  • 8. Decorators
  • 9. Behavioral
  • 10. Structural
  • 11. Creational
  • 12. Practices
  • 13. 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
    • 1.1. Entry Test
    • 1.2. Agenda
    • 1.3. Certificate
  • 2. Protocols
    • 2.1. FTP
    • 2.2. IMAP
    • 2.3. SMTP
    • 2.4. POP3
    • 2.5. LDAP
    • 2.6. SSH
    • 2.7. DNS
  • 3. Web
    • 3.1. HTTP using stdlib
    • 3.2. http.HTTPStatus
    • 3.3. urllib
    • 3.4. http.server
    • 3.5. http.client
    • 3.6. Connecting
    • 3.7. GET Request
    • 3.8. GET Request in chunks
    • 3.9. GET Request to Not Existing Resource
    • 3.10. HEAD Request
    • 3.11. POST Request
    • 3.12. Basic Auth
    • 3.13. Assignments
    • 3.14. HTTP using requests
    • 3.15. HTML Scrapping
    • 3.16. HTTP Frameworks
    • 3.17. FastAPI
    • 3.18. Templates with Jinja2
    • 3.19. PaaS - Platform as a Service
    • 3.20. Asynchronous processing
    • 3.21. SOAP and WSDL
  • 4. Transport
    • 4.1. OSI Model
    • 4.2. Interfaces
    • 4.3. Routing
    • 4.4. Socket
    • 4.5. SSL
    • 4.6. IPv4/IPv6
    • 4.7. TCP/UDP
    • 4.8. scapy
    • 4.9. 3rd Party Libraries
    • 4.10. Mini Botnet

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
  • 2. Jupyter
  • 3. Python
  • 4. Data 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

Object Oriented Programming

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

Blogposts

  • 1. Machine Learning Introduction

Dragon

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

1. About¶

About

  • 1.1. Entry Test
  • 1.2. Agenda
  • 1.3. Certificate

2. Protocols¶

Protocols

  • 2.1. FTP
  • 2.2. IMAP
  • 2.3. SMTP
  • 2.4. POP3
  • 2.5. LDAP
  • 2.6. SSH
  • 2.7. DNS

3. Web¶

Web

  • 3.1. HTTP using stdlib
  • 3.2. http.HTTPStatus
  • 3.3. urllib
  • 3.4. http.server
  • 3.5. http.client
  • 3.6. Connecting
  • 3.7. GET Request
  • 3.8. GET Request in chunks
  • 3.9. GET Request to Not Existing Resource
  • 3.10. HEAD Request
  • 3.11. POST Request
  • 3.12. Basic Auth
  • 3.13. Assignments
  • 3.14. HTTP using requests
  • 3.15. HTML Scrapping
  • 3.16. HTTP Frameworks
  • 3.17. FastAPI
  • 3.18. Templates with Jinja2
  • 3.19. PaaS - Platform as a Service
  • 3.20. Asynchronous processing
  • 3.21. SOAP and WSDL

4. Transport¶

Transport

  • 4.1. OSI Model
  • 4.2. Interfaces
  • 4.3. Routing
  • 4.4. Socket
  • 4.5. SSL
  • 4.6. IPv4/IPv6
  • 4.7. TCP/UDP
  • 4.8. scapy
  • 4.9. 3rd Party Libraries
  • 4.10. Mini Botnet
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© Copyright 2023, CC-BY-SA-4.0, Matt Harasymczuk <matt@astrotech.io>, last update: 2023-03-30 Revision 58d7579f.

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