PyTorch for AI Engineers| Roadmap to Build Transformers & LLMs | Video 1

Scaling Laws Explained Simply (Model, Data, Compute + GPU)

Pre vs Post Layer Normalization

ReLU vs GELU vs Swish (Simple Explanation)

BIG Mistake in Adam | Adam vs AdamW

OPTIMIZERS EXPLAINED

The Secret That Almost Killed AI | Why Transformers Failed in 2018

From Transformers to LLMs: How AI Evolved from 2017 to 2023 | Build AI with Sandeep

Magic of Cross Entropy Loss | Must watch

Why Transformer Decoder Uses Linear + Softmax? (No Confusion Anymore)

Cross Attention Made Easy | Decoder Learns from Encoder

Masked Self-Attention Explained

The Untold Secrets of FFN in Transformers

LayerNorm: The Unknown Hero of Transformers

Self Attention, Multi-Head Attention & Skip Connections Explained Simply and Visually | Transformers

Transformer Encoder Explained with Visuals | Attention, Embedding, PE, Residual Connections

How LLMs Actually Work: The Secret Behind ChatGPT, PaLM & GenAI Explained Simply!

Intro to Gen AI