I create YouTube tutorials, and for each video, I also create a corresponding post featuring code snippets and figures related to the topic. You can find all of these posts in this repository, organized into the following sections:
- Vision Transformers and Their Applications
- Graph Neural Networks
- Self-Supervised Learning
- Neural Radiance Fields (NeRF)
- JAX Performance Tips
- Basic Machine Learning
| Video | Post | Title |
|---|---|---|
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post | Vision Transformers (ViT) PyTorch Code |
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post | Analyzing Swin Transformer: A Code Walkthrough |
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post | A Deep Dive into Swin Transformer Attention Maps |
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post | Vision Transformers (ViT): A JAX Tutorial for Image Classification |
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post | Getting to Know MLP-Mixer: A CIFAR-10 Run |
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post | Fine-tuning Vision Transformers on TPU (ImageNet/CIFAR-10) |
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post | Hands-On with TAPIR: Point Tracking Experiment & Code Walkthrough |
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post | PyTorch Conv2d Explained |
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post | ViT vs CNN: A Comparative Experiment |
| Video | Post | Title |
|---|---|---|
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post | Graph Convolutional Networks (GCNs) in PyTorch |
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post | Graph Sampling for GNNs: A Tutorial |
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post | Exploring LightGCN: A Movie Recommendations Experiment |
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post | Graph Contrastive Learning: Building MovieLens-100k Recommendations |
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post | Understanding Mini-Batch Training in PyTorch Geometric |
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post | Graph Attention Networks with PyTorch Geometric |
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post | Graph Attention Networks with JAX |
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post | Implementing GNN Neighbor Sampler in JAX: A Practical Guide |
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post | Building a Cluster-GCN Model with JAX: A Step-by-Step Guide |
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post | Training GCNs with PyG and Jraph: A Side-by-Side Comparison |
| Video | Post | Title |
|---|---|---|
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post | Inside DINOv2: Architecture Analysis + CIFAR-10 Experiment |
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post | Self-Supervised Learning Review: From SimCLR to DINOv2 |
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post | I-JEPA Explained with a Single Batch Run |
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post | Self-Supervised Learning Collapse: a Quick CIFAR-10 Experiment |
| Video | Post | Title |
|---|---|---|
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post | VGG-SfM and Mip-NeRF 360 Pipeline for iPhone Video 3D Reconstruction |
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post | Exploring Mip-NeRF 360: A Quick TPU Experiment |
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post | Nerfstudio on Lightning AI GPUs |
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post | Structure from Motion (SfM): From COLMAP to VGGSfM |
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post | How NeRF Works: Exploring a Tiny NeRF Code |
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post | 3D Gaussian Splatting: Optimization Explained & Viewer Demo |
| Video | Post | Title |
|---|---|---|
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post | Free TPU Access & JAX/PyTorch Setup with TPU Research Cloud |
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post | Parallel Vision Transformer using JAX Device Mesh |
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post | Experimenting with Different JAX Precisions |
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post | Profiling JAX/XLA with XProf in TensorBoard |
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post | JAX JIT Compilation Explained: From Python to JAXPR |
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post | JAX Conv Layer Explained |
| Video | Post | Title |
|---|---|---|
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post | A Step-by-Step Guide to Spectral Clustering |
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post | JAX and Flax: A Simple Neural Network |
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post | Radial Basis Function (RBF): The Most Popular Kernel in Machine Learning |
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post | Exploring Sparse Subspace Clustering: Theory and Practice |






































