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4 PyTorch Practice Tasks For Beginner AI Researchers - Tutorial youtu.be/NQcXyZOVToE Practice core PyTorch skills with beginner-friendly AI tasks. This tutorial walks through custom layers, learnable parameters, tensor operations, and small neural network building blocks you

4 Transformer PyTorch Tasks For Beginners - Tutorial youtu.be/lD_adTY4XGo Work through beginner transformer tasks in PyTorch. This tutorial covers a simple transformer block, multi-head attention, feed-forward layers, normalization, and the core code structure behind

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DeepSeek V4 RELEASED - Best AI Model Ever DeepSeek V4 Pro and Flash are out, and this video breaks down why the release matters. It covers the model size, benchmark competitiveness against frontier systems, hardware constraints, and what makes this open model notable. Chapters:

Google presents a new Transformer alternative at #ICLR2026! Join Nino Scherrer & Yanick Schimpf at the Google booth (#411) at 10AM to learn about MesaNet, proposing a new linear sequence layer that optimally learns in-context given a fixed memory budget.

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DeepSeek V4 Architecture Explained - Tutorial youtu.be/RVk4fCHbxjI This video breaks down the DeepSeek V4 architecture and the main ideas behind its efficiency gains. It covers the 1 million token context window, mixture-of-experts design, hyperconnections, compressed sparse

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DeepSeek V4 Attention Architecture - Tutorial youtu.be/wVhRLqWYAeU This video breaks down the DeepSeek V4 attention architecture and shows how it balances long-context compression with exact local details. It covers heavily compressed attention, compressed sparse attention,

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Everything I Learned Training Frontier Small Models Maxime Labonne After a lot of hype around frontier model training, Maxime gives the practical version: what actually happens when you try to train smaller models that still matter. From data quality and synthetic data to

Did you know that the embedding layer can contain 63% of total model parameters? 👀 In this talk, I present unique challenges of small models from architecture (⚠️don't build giant embedding layers) to post-training (how to fix doom looping) ↓ Slides in the comments ↓

Day 1 PyTorch From Scratch - Scalar Autograd youtu.be/iPVHKTqfzo4 Chapters: 0:00 Scalars and the value object 1:01 What the value class stores 2:58 Addition and local backward rules 5:29 Multiplication derivative rules 7:23 Building and backpropagating through a tiny graph

If you want to submit an app to the iOS App Store, this course is for you. In it, Shad starts by teaching you how to generate credentials, register your devices, and get your app running. Then he explains how to use CI/CD to push your app to a GitHub repo and automatically

The Kaggle Book, Second Edition by Luca Massaron (Luca Massaron), Bojan Tunguz (Bojan Tunguz), and Konrad Banachewicz is a practical guide to getting better at machine learning through competitive data science. The reason Kaggle still matters is simple: it forces honesty. Your model