A whole lot of new people followed today. Here’s a quick intro - I am Harsh, a Data Scientist based out of Mumbai, India. I started out in the field with no aspirations back in 2020, but fell in love with the game. Learning and sharing on AI/ML, Backend Engineering among other

https://t.co/aQsW59Ylt6, combined with learning help from an LLM, is more accessible than ever. Great way to learn how AI and deep learning really work at the foundations.

Day-27/50 of explaining research papers from ML, DL DEEP COMPRESSION AUTOENCODER FOR EFFICIENT HIGH-RESOLUTION DIFFUSION MODELS @MIT @nvidia > The Deep compression Autoencoder(DC-AE) is introduced as a new high ratio autoencoder architecture for high resolution models

Bro made bank on this one post

We’re starting with this baby today. A lot of topics covered in this, I have, at some point, already worked with. But this is a great formalisation of concepts around LLM based apps and infra > Data Engineering > Ops > Fine tuning (SFT, RL) > Evals > Inference Optimisation

Completing the “Engineer” look before 14 hour screen time kills🙏🏻

The thought, the detail and the effort behind @maninekkalapudi’s sessions are unmatched. And he does it for free. DO NOT miss out !!

Friday afternoon, in a teams meeting, watching some shit cook up here

Follow for more of these 🫡

In the age of LLMs, smart people are getting smarter, while dumb people are getting dumber.

This looks far more useful than agent builder. A sensible, more meaningful solution. Although if Google is involved, say goodbye to your private, proprietary data ☠️

I bought premium after my post blew up and still he thinks I am boosting. Since he thinks so, let's discuss about BOOSTING and BAGGING in detail ( 2 Imp ML techniques ) ✓BAGGING > Works by sampling the dataset with replacement (bootstrapping). >Trains multiple models in

Introducing WORTHUNT - one workspace for creators and agencies Expert Partners - Framer & Lovable Join the Waitlist

Check out their blogs if you are into AI/ML. 1) Andrej Karpathy Neural networks & LLMs explained from first principles by one of the OGs of modern AI. - https://t.co/LKTDzt0IFA 2) Sebastian Raschka, PhD Deep dives into LLM training and fine-tuning with super clear code

We got free threaded python before GTA 6

Read -

If you’re getting into PyTorch, give this a read. It discusses the usability, design patterns and implementation ideas behind the framework. A few bits and pieces that can help you build a good foundation.

https://t.co/dt5uwURuki

Agent Builder is not even in the same stratosphere as n8n. It's like comparing a text editor to a full-blown IDE, or a note-taking app to a word processor. I'm glad OpenAI built this, but it's very, very early to see where this is going. Here is a rough sketch of the way the

Hello, sweet old friend :)

It took me almost 2 years to reach where I am today You can not become an ML engineer in barely 3 months or 6 months. This is a field that requires time, efforts, reiterations and most importantly a lot of patience. Here is your 2-year Q-wise Roadmap to become an MLE 🧵(1/n)