Trainలో Bike పార్శిల్ చేస్తున్నారా..? ఆన్లైన్లోనూ బుకింగ్ చేసుకోవచ్చు..సింపుల్గా ఇలా.
ఇండియన్ రైల్వేస్ ద్వారా మీ బైక్ను అత్యంత తక్కువ ఖర్చుతో, పైగా ఇంట్లో కూర్చునే ఆన్లైన్లో బుక్ చేసి సురక్షితంగా పంపొచ్చు.
స్టెప్-బై-స్టెప్ ప్రాసెస్ & ఫుల్ డీటెయిల్స్ ఇక్కడ చూడండి 👇1/5
Goldmine for AI Engineers! 📌
If you're learning AI, ML, LLMs, or AI agents, don't waste hours jumping between random tutorials.
These are 10 repositories I'd actually keep bookmarked - from Python fundamentals to ML, LLMs, agents, and production AI.
1. Python - 100 Days
jackfrued/Python-100-Days
A 100-day Python learning path covering fundamentals, data analysis, web development, and more.
GitHub:
https://t.co/sw1ujP1Wnp
2. Generative AI for Beginners
microsoft/generative-ai-for-beginners
A practical introduction to building Generative AI applications.
Covers:
• LLM fundamentals
• Prompt engineering
• RAG
• AI agents
• Fine-tuning
• AI application development
GitHub:
https://t.co/xR9iu9EtzU
3. LLMs From Scratch
rasbt/LLMs-from-scratch
Want to understand what's actually happening inside an LLM?
Build one step by step.
Covers:
• Tokenization
• Embeddings
• Attention
• Transformers
• Training
• Fine-tuning
GitHub:
https://t.co/XIZYVfPosz
4. Machine Learning for Beginners
microsoft/ML-For-Beginners
A structured 12-week, 26-lesson curriculum covering classical machine learning.
A good starting point if you want ML fundamentals before jumping into LLMs.
GitHub:
https://t.co/4f85TPlIgv
5. OpenAI Cookbook
openai/openai-cookbook
A collection of practical examples and guides for building applications with OpenAI models.
Useful when you want to move from:
Learning → Building
GitHub:
https://t.co/qQTT34a36j
6. Stable Diffusion
CompVis/stable-diffusion
Interested in generative image models?
This repository contains the original Stable Diffusion implementation and research code.
GitHub:
https://t.co/yy9iV7AMNd
7. AI Agents for Beginners
microsoft/ai-agents-for-beginners
A practical course for understanding and building AI agents.
Covers:
• Agentic AI
• RAG
• Agent frameworks
• Tool use
• Multi-agent systems
GitHub:
https://t.co/kkXpu3tkW7
8. AI for Beginners
microsoft/AI-For-Beginners
A structured 12-week, 24-lesson introduction to AI.
Covers:
• Neural networks
• Computer vision
• NLP
• Deep learning
• Classical AI
GitHub:
https://t.co/uZqsZ77IyP
9. LLM App
pathwaycom/llm-app
Focused on building practical LLM applications.
Explore:
• RAG
• AI pipelines
• Enterprise search
• Real-time data
• Vector search
GitHub:
https://t.co/dKa96swuWu
10. Segment Anything
facebookresearch/segment-anything
A foundation model for promptable image segmentation.
Worth exploring if you're interested in computer vision and multimodal AI.
GitHub:
https://t.co/A22w8WrhZv
Don't bookmark all 10 and forget about them.
Pick based on where you are:
Python → Python-100-Days
ML → ML-For-Beginners
AI Fundamentals → AI-For-Beginners
LLMs → LLMs-from-scratch
Generative AI → Generative-AI-for-Beginners
Agents → AI-Agents-for-Beginners
Building → OpenAI Cookbook / LLM App
Computer Vision → Segment Anything
Pick one.
Build something.
Then move to the next.
Stop telling Claude, "do this."
Stop telling Claude, "write code."
Stop telling Claude, "fix this error."
You're actually treating a senior AI like a junior intern.
Here are 8 prompts you can copy and paste directly:
My wife sent 85 applications. Zero replies.
I uploaded her resume to Claude. 16 responses in 14 days.
Same qualifications. Same experience. Completely different results.
Here are the 7 prompts I used ⤵️
INSTEAD OF WATCHING NETFLIX TONIGHT.
Spend 1 hour with this.
Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything.
The people who watch this tonight will wake up tomorrow with a new skill.
Watch it and Bookmark it now.
INSTEAD OF WATCHING NETFLIX TONIGHT.
Spend 1 hour with this.
Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything.
The people who watch this tonight will wake up tomorrow with a new skill.
Watch it and Bookmark it now.
I've been a backend Engineer for 12+ years. Today, I'm a Principal Engineer at Atlassian.
I've designed systems that handle millions of requests. Sat on both sides of system design interviews.
Reviewed more architecture docs than I can count.
Starting today, I'm breaking down the fundamentals of scaling for the next 25 days.
If you're learning system design bookmark this thread, you're going to get a lot of learning from this.