20:24

How I Got a Job at DeepMind as a Research Engineer (without a Machine Learning Degree!)

01:42

Channel update: moving to London in 2 days, new MLOps series

01:25:47

Coding a Neural Network from Scratch in Pure JAX | Machine Learning with JAX | Tutorial #3

01:08:59

Machine Learning with JAX - From Hero to HeroPro+ | Tutorial #2

01:17:57

Machine Learning with JAX - From Zero to Hero | Tutorial #1

23:32

T0: Multitask Prompted Training Enables Zero-Shot Task Generalization | Paper Explained

24:57

ResNet Strikes Back! | Patches Are All You Need? | Papers Explained

24:36

Fake It Till You Make It (Microsoft) | Paper Explained

16:21

10k subscribers | joining Google DeepMind, updates, AMA

32:54

The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for RL | Paper Explained

30:34

DeepMind Perceiver and Perceiver IO | Paper Explained

39:06

ETA Prediction with Graph Neural Networks in Google Maps | Paper Explained

31:35

Neural Search with Jina AI | Open-source ML Tool Explained

21:54

ALiBi | Train Short, Test Long: Attention With Linear Biases Enables Input Length Extrapolation

48:53

Facebook AI's DINO | PyTorch Code Explained

15:22

Fastformer: Additive Attention Can Be All You Need | Paper Explained

34:51

Do Vision Transformers See Like Convolutional Neural Networks? | Paper Explained

28:54

DeepMind DetCon: Efficient Visual Pretraining with Contrastive Detection | Paper Explained

31:54

DINO: Emerging Properties in Self-Supervised Vision Transformers | Paper Explained!

31:19

DETR: End-to-End Object Detection with Transformers | Paper Explained

03:44

Channel Update: vacation, leaving Microsoft, approaching 10k subs and more!

33:27

DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained

24:41

RMA: Rapid Motor Adaptation for Legged Robots | Paper Explained

24:44

AudioCLIP: Extending CLIP to Image, Text and Audio | Paper Explained

22:39

Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers

21:01

Multimodal Few-Shot Learning with Frozen Language Models | Paper Explained

30:01

VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained

34:38

VQ-VAEs: Neural Discrete Representation Learning | Paper + PyTorch Code Explained

21:08

GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation | Paper Explained

38:41

Graphormer - Do Transformers Really Perform Bad for Graph Representation? | Paper Explained

36:06

Text Style Brush - Transfer of text aesthetics from a single example | Paper Explained

35:41

Chip Placement with Deep Reinforcement Learning | Paper Explained

45:55

Non-Parametric Transformers | Paper explained

23:14

When Vision Transformers Outperform ResNets without Pretraining | Paper Explained

17:46

DeepMind's Android RL Environment - AndroidEnv

28:00

MLP-Mixer: An all-MLP Architecture for Vision | Paper explained

26:38

Implementing DeepMind's DQN from scratch! | Project Update

27:56

EfficientNetV2 - Smaller Models and Faster Training | Paper explained

28:05

MuZero - Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model | RL Paper explained

55:27

OpenAI - Solving Rubik's Cube with a Robot Hand | RL paper explained

41:41

DeepMind's AlphaGo Zero and AlphaZero | RL paper explained

51:24

AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained

51:04

DQN - Playing Atari with Deep Reinforcement Learning | RL Paper Explained

46:31

How to get started with Graph ML? (Blog walkthrough)

40:03

Graph Attention Network Project Walkthrough

08:14

Graph Neural Network Project Update! (I'm coding GAT from scratch)

39:28

Temporal Graph Networks (TGN) | GNN Paper Explained

53:07

OpenAI CLIP - Connecting Text and Images | Paper Explained

50:51

PinSage - Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Paper Explained

43:37

Graph SAGE - Inductive Representation Learning on Large Graphs | GNN Paper Explained

50:04

Graph Convolutional Networks (GCN) | GNN Paper Explained

37:44

Graph Attention Networks (GAT) | GNN Paper Explained

38:45

Attention Is All You Need (Transformer) | Paper Explained

38:30

Google DeepMind's AlphaFold 2 explained! (Protein folding, AlphaFold 1, a glimpse into AlphaFold 2)

46:56

GPT-3 - Language Models are Few-Shot Learners | Paper Explained

24:57

Vision Transformer (ViT) - An image is worth 16x16 words | Paper Explained

31:46

Developing a deep learning project (case study on transformer)

20:12

How do transformers work? (Attention is all you need)

28:20

How to learn deep learning? (Transformers Example)

07:23

Cheapest (0$) Deep Learning Hardware Options | 2021