Forwarded from Machine Learning with Python
Perfect for those who want to level up from
print('Hello') to advanced projects.1. 30-Days-Of-Python — a 30-day Python challenge covering the basics of the language.
2. Python Basics — simple and clear Python basics for beginners.
3. Learn Python — a topic-based guide with examples and code.
4. Python Guide — best practices, tools, and advanced topics.
5. Learn Python 3 — an easy-to-understand guide to Python 3 with practice.
6. Python Programming Exercises — 100+ Python exercises.
7. Coding Problems — algorithmic problems, perfect for interview prep.
8. Project-Based-Learning — learn Python through real projects.
9. Projects — ideas for practical projects and skill improvement.
10. 100-Days-Of-ML-Code — a step-by-step guide to Machine Learning in Python.
11. TheAlgorithms/Python — a huge collection of algorithms in Python.
12. Amazing-Python-Scripts — useful scripts from automation to advanced utilities.
13. Geekcomputers/Python — a collection of practical scripts: networking, files, automation.
14. Materials — code, exercises, and projects from Real Python.
15. Awesome Python — a top list of the best frameworks and libraries.
16. 30-Seconds-of-Python — short snippets for quick solutions.
17. Python Reference — life hacks, tutorials, and useful scripts.
#python #doc #github #soft
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Forwarded from Machine Learning with Python
Design patterns are proven solutions to common problems in development. If you've ever found yourself constantly writing the same thing when creating objects or struggling with managing different types of objects, then the factory pattern might be exactly what you need.
In this tutorial:
https://www.freecodecamp.org/news/how-to-use-the-factory-pattern-in-python-a-practical-guide/
you'll learn what a factory is, why it's useful, and how to implement it in #Python. We'll gather practical examples that will show when and how to apply this pattern in real tasks.
The code can be found on #GitHub
https://github.com/balapriyac/python-basics/tree/main/design-patterns/factory
https://t.me/CodeProgrammer
In this tutorial:
https://www.freecodecamp.org/news/how-to-use-the-factory-pattern-in-python-a-practical-guide/
you'll learn what a factory is, why it's useful, and how to implement it in #Python. We'll gather practical examples that will show when and how to apply this pattern in real tasks.
The code can be found on #GitHub
https://github.com/balapriyac/python-basics/tree/main/design-patterns/factory
https://t.me/CodeProgrammer
❤2👍2
Forwarded from Machine Learning with Python
🗂 Building our own mini-Skynet — a collection of 10 powerful AI repositories from big tech companies
1. Generative AI for Beginners and AI Agents for Beginners
Microsoft provides a detailed explanation of generative AI and agent architecture: from theory to practice.
2. LLMs from Scratch
Step-by-step assembly of your own GPT to understand how LLMs are structured "under the hood".
3. OpenAI Cookbook
An official set of examples for working with APIs, RAG systems, and integrating AI into production from OpenAI.
4. Segment Anything and Stable Diffusion
Classic tools for computer vision and image generation from Meta and the CompVis research team.
5. Python 100 Days and Python Data Science Handbook
A powerful resource for Python and data analysis.
6. LLM App Templates and ML for Beginners
Ready-made app templates with LLMs and a structured course on classic machine learning.
If you want to delve deeply into AI or start building your own projects — this is an excellent starting kit.
tags: #github #LLM #AI #ML
➡️ https://t.me/CodeProgrammer
1. Generative AI for Beginners and AI Agents for Beginners
Microsoft provides a detailed explanation of generative AI and agent architecture: from theory to practice.
2. LLMs from Scratch
Step-by-step assembly of your own GPT to understand how LLMs are structured "under the hood".
3. OpenAI Cookbook
An official set of examples for working with APIs, RAG systems, and integrating AI into production from OpenAI.
4. Segment Anything and Stable Diffusion
Classic tools for computer vision and image generation from Meta and the CompVis research team.
5. Python 100 Days and Python Data Science Handbook
A powerful resource for Python and data analysis.
6. LLM App Templates and ML for Beginners
Ready-made app templates with LLMs and a structured course on classic machine learning.
If you want to delve deeply into AI or start building your own projects — this is an excellent starting kit.
tags: #github #LLM #AI #ML
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