I am a Neuroscientist and Statistician that has become obsessed with AI and I hope to explore different architectures in a way that is accessible to anyone! My goal is to cut through that cloud of mystery that surrounds AI and democratize knowledge about it!

Monte Carlo Methods for Model-Free Learning
43:14
Monte Carlo Methods for Model-Free Learning
UNET From Scratch: Exploring Semantic Segmentation
1:45:41
UNET From Scratch: Exploring Semantic Segmentation
Mathing the Diffusion Model: Where do all those Equations Come From??
1:38:54
Mathing the Diffusion Model: Where do all those Equations Come From??
DCGAN From Scratch
45:13
DCGAN From Scratch
Conditional GAN: Controlling your Generation
36:29
Conditional GAN: Controlling your Generation
Value Iteration
25:47
Value Iteration
Intro to Generative Adversarial Networks
1:00:47
Intro to Generative Adversarial Networks
Mathing the Generative Adversarial Network
48:54
Mathing the Generative Adversarial Network
Policy Iteration
49:23
Policy Iteration
Bellman Optimality Equations
18:20
Bellman Optimality Equations
Mathing the Bellman Equation: Derivation of the Foundational Equation in Reinforcement Learning
37:17
Mathing the Bellman Equation: Derivation of the Foundational Equation in Reinforcement Learning
Residual Vector Quantization (RVQ) From Scratch
49:18
Residual Vector Quantization (RVQ) From Scratch
A Quest to Conquer Reinforcement Learning: Introduction
1:04:44
A Quest to Conquer Reinforcement Learning: Introduction
Vector Quantized Variational AutoEncoder (VQVAE) From Scratch
1:40:09
Vector Quantized Variational AutoEncoder (VQVAE) From Scratch
Llama 4 From Scratch in PyTorch - Vision Language Models + MoE
4:50:07
Llama 4 From Scratch in PyTorch - Vision Language Models + MoE
Lets Reproduce the Vision Transformer on ImageNet
2:12:38
Lets Reproduce the Vision Transformer on ImageNet
Extractive Question Answering: Getting RoBERTa To Answer Questions
1:31:41
Extractive Question Answering: Getting RoBERTa To Answer Questions
Variational AutoEncoders (VAE) Implementation
1:36:55
Variational AutoEncoders (VAE) Implementation
LoRA From Scratch: Finetuning Large Models for Cheaper
2:28:26
LoRA From Scratch: Finetuning Large Models for Cheaper
Mathing the Variational AutoEncoder: Deriving the ELBO Loss
1:20:54
Mathing the Variational AutoEncoder: Deriving the ELBO Loss
Lets Reproduce RoBERTa from Scratch!
3:12:09
Lets Reproduce RoBERTa from Scratch!
Intro To AutoEncoders: Compression is Everything!
1:50:40
Intro To AutoEncoders: Compression is Everything!
Intro to RoBERTa + Masked Language Modeling: Playing Mad Libs Leads to Intelligence!
2:28:10
Intro to RoBERTa + Masked Language Modeling: Playing Mad Libs Leads to Intelligence!
Build + Train the Transformer for Neural Machine Translation!
2:47:46
Build + Train the Transformer for Neural Machine Translation!
Prepping Data for Neural Machine Translation
1:34:55
Prepping Data for Neural Machine Translation
Attention is All You Need: Ditching Recurrence for Good!
3:08:16
Attention is All You Need: Ditching Recurrence for Good!
GPU go brrr: Reproducing ResNet50 using Huggingface 🤗 Accelerate & Distributed Training
2:15:12
GPU go brrr: Reproducing ResNet50 using Huggingface 🤗 Accelerate & Distributed Training
Recurrence for Sequence Generation: Many-to-Many RNN/LSTMs
1:45:59
Recurrence for Sequence Generation: Many-to-Many RNN/LSTMs
Going Deeper with Residual Connections: ResNet Implementation
2:40:36
Going Deeper with Residual Connections: ResNet Implementation
Sequence Modeling: RNN/LSTM for Classification
2:12:53
Sequence Modeling: RNN/LSTM for Classification