🗂 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

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Data Science in Python: a real example

In the video an analysis of data with pandas and matplotlib is shown

https://t.me/Python53 ✅

Python Tip: Operator Overloading

This is a very important concept in Python.

Have you ever wondered how #Python understands what the + operator means? For numbers, it's addition; for strings, it's concatenation; for lists, it's union. This is operator overloading in action.

Operator overloading means defining special behavior for operators (+, -, *, ==, etc.) in your user-defined classes. You determine how these operators should work with your objects.


👉 https://t.me/Python53

🔅 Level Up: Python

📝 Want to test your Python skills? These concise, self-contained challenges let you stretch your brain and test your talents.

📋 Topics: #Python

🗂 20 free MIT courses — the entire Computer Science base in one place

#MIT has made courses in key CS areas publicly available. #Python, #algorithms, #ML, neural networks, #OS, #databases, #mathematics — all can be completed for free directly on #YouTube.

▶️ Introduction to Python Programming
▶️ Data Structures and Algorithms
▶️ Mathematics for Computer Science
▶️ Machine Learning
▶️ Deep Learning
▶️ Artificial Intelligence
▶️ Machine Learning in Healthcare
▶️ Database Management Systems
▶️ Operating Systems
▶️ One-Variable Calculus
▶️ Many-Variable Calculus
▶️ Introduction to Probability Theory
▶️ Statistics
▶️ Probability Theory and Statistics
▶️ Linear Algebra
▶️ Matrix Calculus for Machine Learning
▶️ Java Programming
▶️ Design and Analysis of Algorithms
▶️ Advanced Data Structures
▶️ Introduction to Computational Thinking

tags: #courses

➡https://t.me/python53