Stars
A collection of various deep learning architectures, models, and tips
Repository supporting the training and evaluation of a multimodal neural network for prognostic modeling of soft tissue sarcoma patient outcomes
A curated list of practical guide resources of Medical LLMs (Medical LLMs Tree, Tables, and Papers)
Examples of matplotlib codes and plots
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Interact with the DeepSearch platform for new knowledge explorations and discoveries - Peter Starr IBM
subratac / ML-Course-Notes
Forked from dair-ai/ML-Course-Notes🎓 Sharing course notes on all topics related to machine learning, NLP, and AI.
This is Andrew NG Coursera Handwritten Notes.
Unifying Generative Autoencoder implementations in Python
Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression, multi-objec…
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
subratac / Algorithms-in-Python
Forked from TheAlgorithms/PythonAll Algorithms implemented in Python
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
Nvidia Semantic Segmentation monorepo
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
Segmentation of kidneys on MRI in Autosomal Dominant Polycystic Kidney
subratac / applied-ml
Forked from eugeneyan/applied-ml📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
subratac / CheXbert
Forked from stanfordmlgroup/CheXbertCombining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
subratac / CheXseg
Forked from stanfordmlgroup/CheXsegCode used in the paper "CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation"
pdf, py, and jupyter notebook files for https://pythonhealthcare.org/
Addressing the Discrepancy Between Radiology Report Labels and Image Labels