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Name: Soumyanil Banerjee
Type: User
Company: Postdoctoral Research Fellow, University of Michigan
Bio: Deep Learning, Medical Image Analysis, Computer Vision.
Location: Detroit, MI
Name: Soumyanil Banerjee
Type: User
Company: Postdoctoral Research Fellow, University of Michigan
Bio: Deep Learning, Medical Image Analysis, Computer Vision.
Location: Detroit, MI
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Implementation of Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.
A curated list of awesome Deep Learning tutorials, projects and communities.
A collection of resources and papers on Diffusion Models
Diffusion Models in Medical Imaging
Concept activation vectors for Keras
A complete computer science study plan to become a software engineer.
CSC 7991 Deep Learning Project
Set of Jupyter Notebooks linked to Roboflow Blogpost and used in our YouTube videos.
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
Official TensorFlow implementation of Deep Relational Reasoning for prediction of language impairments and seizure outcomes
neuralnetworksanddeeplearning.com integrated scripts for Python 3.5.2 and Theano with CUDA support
This repository categorizes the papers about diffusion models applied in computer vision according to their target task. The classifcation is based on our survey: https://arxiv.org/abs/2209.04747v1
Official PyTorch implementation of Dual Self-Distillation (DSD) in U-shaped Networks for Medical Image Segmentation
The fastai book, published as Jupyter Notebooks
Gaussian Naive Bayes (GaussianNB) classifier
MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications
Must-read papers on graph neural networks (GNN)
Build Graph Nets in Tensorflow
Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.
Histocartography is a framework bringing together AI and Digital Pathology
This repository contains the code for implementing Bidirectional Relevance scores for Digital Histopathology, which was used for the results in the iMIMIC workshop paper: Regression Concept Vectors for Bidirectional Explanations in Histopathology
Welcome to Keras Deep Learning on Graphs (Keras-DGL) http://vermaMachineLearning.github.io/keras-deep-graph-learning
Python & JAVA Solutions for Leetcode
:octocat: (Weekly Update) Python / C++ 11 Solutions of All 1172 LeetCode Problems
A comprehensive collection of recent papers on graph deep learning
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.