⚡️ All cheat sheets for programmers in one place.

There's a lot of useful stuff inside: short, clear tips on languages, technologies, and frameworks.

No registration required and it's free.

https://overapi.com/

#python #php #Database #DataAnalysis #MachineLearning #AI #DeepLearning #LLMS

https://xn--r1a.website/CodeProgrammer ⚡️

These 9 lectures from Stanford are a pure goldmine for anyone wanting to learn and understand LLMs in depth

Lecture 1 - Transformer: https://lnkd.in/dGnQW39t

Lecture 2 - Transformer-Based Models & Tricks: https://lnkd.in/dT_VEpVH

Lecture 3 - Tranformers & Large Language Models: https://lnkd.in/dwjjpjaP

Lecture 4 - LLM Training: https://lnkd.in/dSi_xCEN

Lecture 5 - LLM tuning: https://lnkd.in/dUK5djpB

Lecture 6 - LLM Reasoning: https://lnkd.in/dAGQTNAM

Lecture 7 - Agentic LLMs: https://lnkd.in/dWD4j7vm

Lecture 8 - LLM Evaluation: https://lnkd.in/ddxE5zvb

Lecture 9 - Recap & Current Trends: https://lnkd.in/dGsTd8jN

Start understanding #LLMs in depth from the experts. Go through each step-by-step video.

https://xn--r1a.website/DataAnalyticsX 🔗

🤖 Best GitHub repositories to learn AI from scratch in 2026

If you want to understand AI not through "vacuum" courses, but through real open-source projects - here's a top list of repos that really lead you from the basics to practice:

1) Karpathy – Neural Networks: Zero to Hero 
The most understandable introduction to neural networks and backprop "in layman's terms"
https://github.com/karpathy/nn-zero-to-hero

2) Hugging Face Transformers 
The main library of modern NLP/LLM: models, tokenizers, fine-tuning 
https://github.com/huggingface/transformers

3) FastAI – Fastbook 
Practical DL training through projects and experiments 
https://github.com/fastai/fastbook

4) Made With ML 
ML as an engineering system: pipelines, production, deployment, monitoring 
https://github.com/GokuMohandas/Made-With-ML

5) Machine Learning System Design (Chip Huyen) 
How to build ML systems in real business: data, metrics, infrastructure 
https://github.com/chiphuyen/machine-learning-systems-design

6) Awesome Generative AI Guide 
A collection of materials on GenAI: from basics to practice 
https://github.com/aishwaryanr/awesome-generative-ai-guide

7) Dive into Deep Learning (D2L) 
One of the best books on DL + code + assignments 
https://github.com/d2l-ai/d2l-en

Save it for yourself - this is a base on which you can really grow into an ML/LLM engineer.

#Python #datascience #DataAnalysis #MachineLearning #AI #DeepLearning #LLMS

https://xn--r1a.website/CodeProgrammer