rainwaint's starred repositories
Deep_reinforcement_learning_Course
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Reinforcement-Learning-Notebooks
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.
Reinforcement_Learning_for_Stock_Prediction
This is the code for "Reinforcement Learning for Stock Prediction" By Siraj Raval on Youtube
stocks_rnn
Stock price prediction with LSTMs in TensorFlow
UNet-CRF-RNN
Edge-aware U-Net with CRF-RNN layer for Medical Image Segmentation
rl-medical
Communicative Multiagent Deep Reinforcement Learning for Anatomical Landmark Detection using PyTorch.
django_documentation
Russian translation of Django documentation
MedicalReportGeneration
A Base Tensorflow Project for Medical Report Generation
Zero-Learning-Fast-Medical-Image-Fusion
An OpenCV and Pytorch implementation of Zero-Learning-Fast-Medical-Image-Fusion
Chest-X-Ray-Image_Segmentation_ResUNet
Lung segmentation for chest X-Ray images with ResUNet and UNet. In addition, feature extraction and tuberculosis cases diagnosis had developed.
cnn-cell-counting
A machine learning model using CNN to count number of cells in a medical image
Yandex_Practicum_DataScience
Проекты из Яндекс Практикума "Специалист по Data Science"
Yandex-Data-Analysis
Репозиторий учебных проектов из Яндекс Практикум "Аналитик данных"
School21-Golang-Piscine
Mad intensive course from Moscow campus of intra42
Medical-Image-Segmentation-DL
Implemented Unet++ models for medical image segmentation to detect and classify colorectal polyps.
Digital-Image-Processing-for-Medical-Applications
Challenge Project In Ecole Centrale Casablanca - Learning by doing
CM2003-Deep-Learning-Methods-for-Medical-Image-Analysis.
The course is offered by KTH in Autumn semester and and focuses on Medical image segmentation using CNN and hands-on section with TensorFlow, ,medical image classification using CNN and hands-on section with TensorFlow, medical image analysis using RNN and hands-on section with TensorFlow
medical_image_segmentation
Medical Image Segmentation using CNNs and RNNs, especially U-Net, RU-Net and R2U-Net
Pytorch_Segnet_DeepLabV3
This notebook is a tutorial for image semantic segmentation using Segnet and DeepLabv3 in Pytorch . Its a starter code as a part of Severstal Steel Detection https://www.kaggle.com/c/severstal-steel-defect-detection in Kaggle .
Medical_Segmentation
3D modeling of the aortic arch, based on medical images ; for preoperative planning assistance in interventional neurology (Python, Qt, OpenCv, VTK).
Recurrent-Neural-Network-PyTorch
This repository contains a Jupyter Notebook showcasing the implementation of a Recurrent Neural Network (RNN) using PyTorch for image classification.
medical_Image_OpenCV
using OpenCV to deal with medical images
Neural-network_1
Нейронные сети_1
machine_learning_end_to_end
Notebooks on CNN(classification, transfer learning, image segmentation) / BERT / RNN(LSTM and GRU) / CBOW/ ANN / Classical ML(hyperparameter tuning/ classification)
crf-rnn-network
Сегментация изображений с помощью сети crf-rnn
Image-Segmantation-usingUnet
I segmented the image containing people and found that U-Net is one of the best tool for segmentation of images. Unet is an improvement of the CNN model which specializes in image segmentation