Build NanoVLM from scratch
Coding Swin transformer from scratch
VisualBERT paper dissection
Swin transformer paper dissection - Hierarchical Vision Transformer using Shifted Windows
Input, output and filter dimensions in 2D convolution
Introduction to Swin transformer
Dissecting DeiT paper - Data efficient image Transformer
Coding DeiT Data Efficient Image Transformer from scratch
Full compilation- Swin transformer intuition + coding from scratch
Contrastive learning for Vision Language Models
Introduction to Vision Language Models (VLM)
Vision Transformer paper dissection
Build Vision Transformer ViT From Scratch - Intuition and coding
Let us hand-calculate how GPT-3 has a total of 175B parameters | Transformers for Vision
Implementing multi head attention with tensors | Avoiding loops to enable LLM scale-up
Introduction to Multi head attention
Understanding causal attention or masked self attention | Transformers for vision series
Introduction to Flamingo VLM: Understanding the architecture and running inference
Reading JEPA paper (Yann LeCun co-author) | Joint Embedding Predictive Architecture
Full 3-hour compilation - Diffusion model (DDPM) - Intuition + Coding from scratch
Diffusion model (DDPM) PART 2 - Coding from scratch
Diffusion model (DDPM) PART 1 - theory and intuition
Full 3 hour compilation | Autoencoder + VAE | Intuition + coding from scratch
Variational Autoencoder [VAE] from scratch | Intuition + Coding
Autoencoder from scratch in 60 minutes | Intuition + coding
LLaVA paper - Comprehensive dissection
Q, K, V intuition | Introduction to self attention with trainable weights
Flamingo paper - Comprehensive dissection
Full 6.5-hour compilation: Transformers for Detection and Segmentation - DETR and SAM from scratch
Full 4-hour compilation: Detection Transformer (DETR) intuition + coding
TimeSformer from scratch: How to use Vision Transformer (ViT) for videos?
Segment Anything Model (SAM): An introduction
Coding Detection Transformer (DETR)
Detection Transformer DETR intuition
ViT + DeiT + Swin transformers | Full 10 hour compilation | Intuition + coding from scratch
VGGNet: The legendary paper with 145k citations threatened the dominance of AlexNet| Computer Vision
Introduction to Vision Transformer (ViT) | An image is worth 16x16 words | Computer Vision Series
A Historical Journey through CNNs and Modern Computer Vision 2010–2025 | Computer Vision Series
Use Neural Network to find a good CNN Architecture - NASNet | Computer Vision Series
DenseNet and EfficientNet - How CNNs were made better and better | Computer Vision Series
MobileNet - Deep Learning that fits in your pocket | Convolutional Neural Network | Computer Vision
ResNet Explained - Vanishing Gradients, Skip Connections, and Code Implementation | Computer Vision
The Story of SqueezeNet: Why Smaller CNNs Can Be Smarter? | Computer Vision Series
GoogleNet (aka Inception V1) | The legendary CNN model that ranked #1 in ImageNet 2014 | CV Series
Coding a Vision Transformer from scratch using PyTorch
AlexNet - the neural network that transformed Computer Vision | Convolution, Pooling and Deep NN
Transfer learning: Pretrained embedding, fine-tuning, differential learning | Computer Vision Series
Overfit prevention - Regularization, Dropout, Early Stopping, Batch Normalization | Computer Vision
Hyperparameter Tuning Like a Pro: W&B for Your ML Experiments | Computer Vision Series [Lecture 5]
Neural network for image classification | Computer Vision from Scratch series [Lecture 4]
A simple neural network for computer vision | CV from scratch series [Lecture 3]
Introduction to filters and convolution | Computer vision from scratch series [Lecture 2]
Introduction to Computer Vision | Lecture 1 | CV from scratch series
YOLO + OCR for License Plate Recognition | Computer Vision Hands-on Project
Introduction to self attention | Implementing a simplified self-attention | Transformers for Vision
From RNNs to Transformers - Introduction to attention mechanism | Transformers for Vision
The journey of a single token - Introduction to LLMs | Transformers for Vision Series
How transformer took over computer vision? CNN's struggle with long range dependency
New Series Launch | Transformers for Vision and Multimodal LLMs | Lecture 1
Build and deploy Computer Vision Model for fall detection | Roboflow + Streamlit | Physical Safety
Computer Vision Bootcamp | Full 12 hour series | OpenCV, RCNN, UNet, YOLO and Roboflow
Roboflow - Best way to build end-to-end computer vision pipeline
Computer Vision from Scratch | New course launch | By MIT PhD | Foundations and practical CV
A beginners introduction to YOLO | You Only Look Once | Computer Vision
UNet and its Family: UNet++, Residual UNet, and Attention UNet | Computer Vision Bootcamp
UNet: the 2015 model with 118k+ citations that changed segmentation - And how GenAI brought it back
Introduction to Mask R-CNN for image segmentation | Computer Vision bootcamp
Object Detection using R-CNN, Fast R-CNN, and Faster R-CNN | Computer Vision Hands-on Bootcamp
Object tracking and Counting | OpenCV + YOLO | Computer Vision Hands-on bootcamp
Hands on Computer Vision Bootcamp | Day 1
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