paneerchilli65
3.8K posts

paneerchilli65
@paneerchilli65
grind feels like melamine | 2x |
bbsr Katılım Haziran 2024
1.5K Takip Edilen1.9K Takipçiler

I came across this blog from Chip Huyen in 2022 where she discussed the ai courses to do. i feel they are relevant to this day!
Here they are -
STATS 202 :- data mining basics
CS109 :- probability foundations
CS231N :- computer vision DL
CS224N :- NLP deep learning
CS229 :- theoretical machine learning
CS221 :- intro artificial intelligence
CS228 :- probabilistic graphical models
CS234 :- reinforcement learning
CS238 :- decision theory RL
CS224W :- graph machine learning
CS246 :- large-scale data mining
CS230 :- applied deep learning
CS236 :- generative models
EE263 :- linear dynamical systems
CS336 :- robot perception
CS103 :- discrete math foundations
CS124 :- NLP basics
CS223A :- robotics fundamentals
i have done a few from here, would reccomend
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@Hi_Mrinal coldemailing doesn't work in 2026.
tbh best alternative to coldmailing this days is just join their discord server and talk about how to improve the product.
easier way to directly talk to orgs entire team and caught the attention.
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So I was one of many who bookmarked this post and thought to shoot my shot out of nowhere :p

GIF
Kimi.ai@Kimi_Moonshot
Come introduce yourself to the team, we have your slippers ready. Reach out at: talent@moonshot.ai
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Wrote a deep dive on implementing a language model from scratch in JAX and scaling it with distributed training!
If you’re coming from PyTorch and want to see how the same ideas look in JAX, or just want a hands-on intro to distributed training, check out this blog post: chuyishang.com/blog/2026/jax-…
Comes with code + an assignment and test cases so you can follow along!


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@kmeanskaran demand forecasting for rl, slms for iot devices and intraday would become very good projects/products 😁
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Before it's too late, learn any of these skills to become elite AI/ML Engineer:
- Maths focused AI research
- Data Engineering with distribution
- AI Agents orchestration
- Multi-GPU training
- Inference optimization
- Demand Forecasting with RL
- MLOps and AgentOps
- SLMs for IoT devices
- Deployment on cloud
- System Design for ML
- Data drift detection
- Rollback and task queues for ML
- Backend for AI
- Vision Transformers in IoT
- Quant and Intraday using ML
The most important skill is using minimal setup with high impact on business more than just ML metrics.
Also, important part is just deliver projects within less span by iterative release.
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longer runs-->
num-stories 50000, no of steps 100k, adamw
after 6 failed runs the training worked for 2xt4s
paneerchilli65@paneerchilli65
first try of making a micro-diffusion llm trained on shakespeare text for 5k steps with char level tokenizer
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@freshlimesofa bhai llama ke jagah qwen 3.5 hi use kar lete
हिन्दी

I did something interesting today.
A recent project that I worked on had a Text-to-SQL agent,
While testing on local using Ollama, we used a 3B version of Llama that failed pretty bad at SQL gen despite a pretty good prompt (an 8B version did work tho)
I took the 3B model and prepared a dataset of natural language vs SQL with respect to our database schema and decided to perform SFT with LoRA.
The result was pretty good, it generated executable SQL queries apt to the schema.
Will download the GGUF and hook it up to the application tomorrow, should work !!

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@freshlimesofa Datasets
#repos" target="_blank" rel="nofollow noopener">huggingface.co/TeichAI/datase…
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Jadeja experimenting with a carrom ball - if you look closely.
Rajasthan Royals@rajasthanroyals
🗡️🆚🥶
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