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Uniform Manifold Approximation and Projection (UMAP) | Dimensionality Reduction Techniques (5/5)
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t-distributed Stochastic Neighbor Embedding (t-SNE) | Dimensionality Reduction Techniques (4/5)
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t-distributed Stochastic Neighbor Embedding (t-SNE) | Dimensionality Reduction Techniques (4/5)
31:20
Multidimensional Scaling (MDS) | Dimensionality Reduction Techniques (3/5)
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Multidimensional Scaling (MDS) | Dimensionality Reduction Techniques (3/5)
30:12
Principal Component Analysis (PCA) | Dimensionality Reduction Techniques (2/5)
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Principal Component Analysis (PCA) | Dimensionality Reduction Techniques (2/5)
26:17
Dimensionality Reduction Techniques | Introduction and Manifold Learning (1/5)
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Dimensionality Reduction Techniques | Introduction and Manifold Learning (1/5)
13:10
LoRA explained (and a bit about precision and quantization)
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LoRA explained (and a bit about precision and quantization)
17:07
Vision Transformer Quick Guide - Theory and Code in (almost) 15 min
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Vision Transformer Quick Guide - Theory and Code in (almost) 15 min
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Personalized Image Generation (using Dreambooth) explained!
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Personalized Image Generation (using Dreambooth) explained!
17:45
Equivariant Neural Networks | Part 3/3 - Transformers and GNNs
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Equivariant Neural Networks | Part 3/3 - Transformers and GNNs
16:19
Equivariant Neural Networks | Part 2/3 - Generalized CNNs
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Equivariant Neural Networks | Part 2/3 - Generalized CNNs
15:57
Equivariant Neural Networks | Part 1/3 - Introduction
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Equivariant Neural Networks | Part 1/3 - Introduction
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State of AI 2022 - My Highlights
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State of AI 2022 - My Highlights
9:33
Contrastive Learning in PyTorch - Part 2: CL on Point Clouds
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Contrastive Learning in PyTorch - Part 2: CL on Point Clouds
27:20
Contrastive Learning in PyTorch - Part 1: Introduction
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Contrastive Learning in PyTorch - Part 1: Introduction
14:21
Self-/Unsupervised GNN Training
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Self-/Unsupervised GNN Training
12:09
Diffusion models from scratch in PyTorch
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Diffusion models from scratch in PyTorch
30:54
Causality and (Graph) Neural Networks
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Causality and (Graph) Neural Networks
16:13
How to get started with Data Science (Career tracks and advice)
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How to get started with Data Science (Career tracks and advice)
14:15
Converting a Tabular Dataset to a Temporal Graph Dataset for GNNs
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Converting a Tabular Dataset to a Temporal Graph Dataset for GNNs
18:11
Converting a Tabular Dataset to a Graph Dataset for GNNs
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Converting a Tabular Dataset to a Graph Dataset for GNNs
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How to handle Uncertainty in Deep Learning #2.2
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How to handle Uncertainty in Deep Learning #2.2
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How to handle Uncertainty in Deep Learning #2.1
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How to handle Uncertainty in Deep Learning #2.1
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How to handle Uncertainty in Deep Learning #1.2
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How to handle Uncertainty in Deep Learning #1.2
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How to handle Uncertainty in Deep Learning #1.1
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How to handle Uncertainty in Deep Learning #1.1
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Recommender Systems using Graph Neural Networks
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Recommender Systems using Graph Neural Networks
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Fake News Detection using Graphs with Pytorch Geometric
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Fake News Detection using Graphs with Pytorch Geometric
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Fraud Detection with Graph Neural Networks
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Fraud Detection with Graph Neural Networks
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Traffic Forecasting with Pytorch Geometric Temporal
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Traffic Forecasting with Pytorch Geometric Temporal
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Friendly Introduction to Temporal Graph Neural Networks (and some Traffic Forecasting)
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Friendly Introduction to Temporal Graph Neural Networks (and some Traffic Forecasting)
14:26
Python Graph Neural Network Libraries (an Overview)
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Python Graph Neural Network Libraries (an Overview)
11:09
Explaining Twitch Predictions with GNNExplainer
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Explaining Twitch Predictions with GNNExplainer
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How to explain Graph Neural Networks (with XAI)
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How to explain Graph Neural Networks (with XAI)
15:07
Machine Learning Model Deployment with Python (Streamlit + MLflow) | Part 2/2
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Machine Learning Model Deployment with Python (Streamlit + MLflow) | Part 2/2
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Machine Learning Model Deployment with Python (Streamlit + MLflow) | Part 1/2
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Machine Learning Model Deployment with Python (Streamlit + MLflow) | Part 1/2
10:01
GNN Project #4.3 - Code explanation
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GNN Project #4.3 - Code explanation
18:36
GNN Project #4.3 - One-shot molecule generation - Part 1
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GNN Project #4.3 - One-shot molecule generation - Part 1
15:54
GNN Project #4.2 - GVAE Training and Adjacency reconstruction
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GNN Project #4.2 - GVAE Training and Adjacency reconstruction
27:09
GNN Project #4.1 - Graph Variational Autoencoders
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GNN Project #4.1 - Graph Variational Autoencoders
12:53
GNN Project #3.2 - Graph Transformer
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GNN Project #3.2 - Graph Transformer
14:03
GNN Project #3.1 - Graph-level predictions
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GNN Project #3.1 - Graph-level predictions
18:34
GNN Project #2 - Creating a Custom Dataset in Pytorch Geometric
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GNN Project #2 - Creating a Custom Dataset in Pytorch Geometric
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GNN Project #1 - Introduction to HIV dataset
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GNN Project #1 - Introduction to HIV dataset
3:09
Understanding Graph Attention Networks
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Understanding Graph Attention Networks
15:00
Explainable AI explained! | #6 Layerwise Relevance Propagation with MRI data
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Explainable AI explained! | #6 Layerwise Relevance Propagation with MRI data
28:28
Explainable AI explained! | #5 Counterfactual explanations and adversarial attacks
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Explainable AI explained! | #5 Counterfactual explanations and adversarial attacks
16:57
Explainable AI explained! | #4 SHAP
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Explainable AI explained! | #4 SHAP
15:50
Explainable AI explained! | #3 LIME
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Explainable AI explained! | #3 LIME
13:59
Explainable AI explained! | #2 By-design interpretable models with Microsofts InterpretML
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Explainable AI explained! | #2 By-design interpretable models with Microsofts InterpretML
20:54
Explainable AI explained! | #1 Introduction
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Explainable AI explained! | #1 Introduction
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How to use edge features in Graph Neural Networks (and PyTorch Geometric)
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How to use edge features in Graph Neural Networks (and PyTorch Geometric)
16:48
Understanding Convolutional Neural Networks | Part 3 / 3 - Transfer Learning and Explainable AI
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Understanding Convolutional Neural Networks | Part 3 / 3 - Transfer Learning and Explainable AI
25:33
Understanding Convolutional Neural Networks | Part 2 / 3 - Wonders of the world CNN with PyTorch
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Understanding Convolutional Neural Networks | Part 2 / 3 - Wonders of the world CNN with PyTorch
29:15
Understanding Convolutional Neural Networks | Part 1 / 3 - The Basics
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Understanding Convolutional Neural Networks | Part 1 / 3 - The Basics
19:59
Node Classification on Knowledge Graphs using PyTorch Geometric
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Node Classification on Knowledge Graphs using PyTorch Geometric
18:51
Understanding Graph Neural Networks | Part 3/3 - Pytorch Geometric and Molecule Data using RDKit
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Understanding Graph Neural Networks | Part 3/3 - Pytorch Geometric and Molecule Data using RDKit
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Understanding Graph Neural Networks | Part 2/3 - GNNs and it's Variants
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Understanding Graph Neural Networks | Part 2/3 - GNNs and it's Variants
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Understanding Graph Neural Networks | Part 1/3 - Introduction
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Understanding Graph Neural Networks | Part 1/3 - Introduction
8:18