You will often see me writing about research papers (mostly in the field of Computer Vision) explaining them in a simple language in theory along with their PyTorch Implementation. Please feel free to subscribe to receive regular updates regarding new blog posts.
During my time as Machine Learning Engineer at Weights and Biases, I also wrote the following blog posts:
| Title | Link |
|---|---|
| Explained: Characterizing Signal Propagation to Close the Performance Gap in Unnormalized ResNets | [link] |
| Revisiting ResNets: Improved Training and Scaling Strategies | [link] |
| ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases | [link] |
| Is MLP-Mixer a CNN in Disguise? | [link] |
| Are fully connected and convolution layers equivalent? If so, how? | [link] |
| A faster way to get working and up-to-date conda environments using “fastchan” | [link] |
| Inside Hugging Face’s Accelerate! | [link] |
The Annotated CLIP (Part-2)
This post is part-2 of the two series blog posts on CLIP (for part-1, please refer to my previous blog post). In this blog, we present the PyTorch code behind CLIP for model building and training. This blog post is in itself a working Jupyter Notebook.
The Annotated CLIP (Part-1)
This post is part-1 of the two series blog posts on CLIP. In this blog, we present an Introduction to CLIP in an easy to digest manner. We also compare CLIP to other research papers and look at the background and inspiration behind CLIP.
Swin Transformer
Swin Transformer Model Architecture explained with PyTorch implementation line-by-line.
The Annotated DETR
DETR Model Architecture explained with PyTorch implementation line-by-line.
The EfficientDet Architecture in PyTorch
In this blog post, we will look at how to implement the EfficientDet architecture in PyTorch from scratch.
EfficientDet - Scalable and Efficient Object Detection
As part of this blog post I will explain how EfficientDets work step-by-step.
Top 100 solution - SIIM-ACR Pneumothorax Segmentation
In this blog post, we will looking at Image Segmentation based problem in Pytorch with SIIM-ACR Pneumothorax Segmentation competition serving as a useful example and create a solution that will get us to the top-100 leaderboard position on Kaggle.
GeM Pooling Explained with PyTorch Implementation and Introduction to Image Retrieval
As part of this blog post we will be looking at GeM pooling and also look at the research paper Fine-tuning CNN Image Retrieval with No Human Annotation. We also implement GeM Pooling from scratch in PyTorch.
U-Net A PyTorch Implementation in 60 lines of Code
As part of this blog post we will implement the U-Net architecture in PyTorch in 60 lines of code.
EfficientNet
Look at the current SOTA, with top-1 accuracy of 88.5% on ImageNet.
An introduction to PyTorch Lightning with comparisons to PyTorch
In this blogpost, we will be going through an introduction to Pytorch Lightning and implement all the cool tricks like - Gradient Accumulation, 16-bit precision training, and also add TPU/multi-gpu support - all in a few lines of code. We will use Pytorch Lightning to work on SIIM-ISIC Melanoma Classification challenge on Kaggle.
