Raman Dutt's starred repositories
ambient-tweedie
[ICML 2024]: Official implementation for the paper: "Consistent Diffusion Meets Tweedie"
CheXclusion
Code for the paper https://arxiv.org/abs/2003.00827
OneTrainer
OneTrainer is a one-stop solution for all your stable diffusion training needs.
ml-engineering
Machine Learning Engineering Open Book
FriendsDontLetFriends
Friends don't let friends make certain types of data visualization - What are they and why are they bad.
awesome-medical-vision-language-models
A collection of resources on Medical Vision-Language Models
unetr_plus_plus
[IEEE TMI-2024] UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation
transdeeplab
TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation
vnet.pytorch
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
Personalize-SAM
Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds
svdiff-pytorch
Implementation of "SVDiff: Compact Parameter Space for Diffusion Fine-Tuning"
Grounded-Segment-Anything
Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
minimal-ml-template
A very minimal ml project template that uses HF transformers and wandb to train a simple NN and evaluate it, in a stateless manner compatible with Spot instances kubernetes workflows
Awesome-Parameter-Efficient-Transfer-Learning
A collection of parameter-efficient transfer learning papers focusing on computer vision and multimodal domains.
EfficientUnet-PyTorch
A PyTorch 1.0 Implementation of Unet with EfficientNet as encoder
ifsFractals-py
A Python module for fast IFS fractal generation.
RadImageNet
RadImageNet, a pre-trained convolutional neural networks trained solely from medical imaging to be used as the basis of transfer learning for medical imaging applications.
machine-learning-interview
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
AutoAugment
Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow