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Flash Attention derived and coded from first principles with Triton (Python)

70k

PT5H46M5S

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation

Umar JamilAug 7, 2024

114k

PT1H15S

ML Interpretability: feature visualization, adversarial example, interp. for language models

Umar JamilMay 21, 2024

12k

PT1H15M39S

Kolmogorov-Arnold Networks: MLP vs KAN, Math, B-Splines, Universal Approximation Theorem

Umar JamilMay 11, 2024

38k

PT48M46S

Direct Preference Optimization (DPO) explained: Bradley-Terry model, log probabilities, math

Umar JamilApr 14, 2024

33k

PT2H15M13S

Reinforcement Learning from Human Feedback explained with math derivations and the PyTorch code.

Umar JamilFeb 27, 2024

60k

PT1H14M29S

Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math

Umar JamilJan 7, 2024

58k

PT1H26M21S

Mistral / Mixtral Explained: Sliding Window Attention, Sparse Mixture of Experts, Rolling Buffer

Umar JamilDec 27, 2023

39k

PT1H12M53S

Distributed Training with PyTorch: complete tutorial with cloud infrastructure and code

Umar JamilDec 19, 2023

31k

PT21M12S

How diffusion models work - explanation and code!

Umar JamilDec 19, 2023

30k

PT50M55S

Quantization explained with PyTorch - Post-Training Quantization, Quantization-Aware Training

Umar JamilDec 18, 2023

47k

PT49M24S

Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)

Umar JamilNov 27, 2023

81k

PT54M52S

BERT explained: Training, Inference, BERT vs GPT/LLamA, Fine tuning, [CLS] token

Umar JamilOct 26, 2023

72k

PT5H3M32S

Coding Stable Diffusion from scratch in PyTorch

Umar JamilSep 27, 2023

209k

PT3H4M11S

Coding LLaMA 2 from scratch in PyTorch - KV Cache, Grouped Query Attention, Rotary PE, RMSNorm

Umar JamilSep 3, 2023

62k

PT1H10M55S

LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU

Umar JamilAug 24, 2023

107k

PT42M53S

Segment Anything - Model explanation with code

Umar JamilAug 14, 2023

36k

PT26M55S

LoRA: Low-Rank Adaptation of Large Language Models - Explained visually + PyTorch code from scratch

Umar JamilJul 25, 2023

46k

PT29M58S

LongNet: Scaling Transformers to 1,000,000,000 tokens: Python Code + Explanation

Umar JamilJul 15, 2023

6.9k

PT27M12S

Variational Autoencoder - Model, ELBO, loss function and maths explained easily!

Umar JamilJun 7, 2023

61k

PT58M4S

Attention is all you need (Transformer) - Model explanation (including math), Inference and Training

Umar JamilMay 28, 2023

645k

Featured Results

Titans: Learning to Memorize at Test Time

Paper: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Flash Attention derived and coded from first principles with Triton (Python)

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation

ML Interpretability: feature visualization, adversarial example, interp. for language models

Kolmogorov-Arnold Networks: MLP vs KAN, Math, B-Splines, Universal Approximation Theorem

Direct Preference Optimization (DPO) explained: Bradley-Terry model, log probabilities, math

Reinforcement Learning from Human Feedback explained with math derivations and the PyTorch code.

Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math

Mistral / Mixtral Explained: Sliding Window Attention, Sparse Mixture of Experts, Rolling Buffer

Distributed Training with PyTorch: complete tutorial with cloud infrastructure and code

How diffusion models work - explanation and code!

Quantization explained with PyTorch - Post-Training Quantization, Quantization-Aware Training

Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)

BERT explained: Training, Inference, BERT vs GPT/LLamA, Fine tuning, [CLS] token

Coding Stable Diffusion from scratch in PyTorch

Coding LLaMA 2 from scratch in PyTorch - KV Cache, Grouped Query Attention, Rotary PE, RMSNorm

LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU

Segment Anything - Model explanation with code

LoRA: Low-Rank Adaptation of Large Language Models - Explained visually + PyTorch code from scratch

LongNet: Scaling Transformers to 1,000,000,000 tokens: Python Code + Explanation

Variational Autoencoder - Model, ELBO, loss function and maths explained easily!

Attention is all you need (Transformer) - Model explanation (including math), Inference and Training

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Featured Results

Titans: Learning to Memorize at Test Time

Paper: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Flash Attention derived and coded from first principles with Triton (Python)

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation

ML Interpretability: feature visualization, adversarial example, interp. for language models

Kolmogorov-Arnold Networks: MLP vs KAN, Math, B-Splines, Universal Approximation Theorem

Direct Preference Optimization (DPO) explained: Bradley-Terry model, log probabilities, math

Reinforcement Learning from Human Feedback explained with math derivations and the PyTorch code.

Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math

Mistral / Mixtral Explained: Sliding Window Attention, Sparse Mixture of Experts, Rolling Buffer

Distributed Training with PyTorch: complete tutorial with cloud infrastructure and code

How diffusion models work - explanation and code!

Quantization explained with PyTorch - Post-Training Quantization, Quantization-Aware Training

Retrieval Augmented Generation (RAG) Explained: Embedding, Sentence BERT, Vector Database (HNSW)

BERT explained: Training, Inference, BERT vs GPT/LLamA, Fine tuning, [CLS] token

Coding Stable Diffusion from scratch in PyTorch

Coding LLaMA 2 from scratch in PyTorch - KV Cache, Grouped Query Attention, Rotary PE, RMSNorm

LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU

Segment Anything - Model explanation with code

LoRA: Low-Rank Adaptation of Large Language Models - Explained visually + PyTorch code from scratch

LongNet: Scaling Transformers to 1,000,000,000 tokens: Python Code + Explanation

Variational Autoencoder - Model, ELBO, loss function and maths explained easily!

Attention is all you need (Transformer) - Model explanation (including math), Inference and Training

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