bit-whacker

awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

bitcoin_volatility_forecasting

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

CGGA

Cancer subtype identification by consensus guided graph autoencoder

clinical-notes-diagnosis-dl-nlp

cnn-from-scratch

A Convolutional Neural Network implemented from scratch (using only numpy) in Python.

CryptocurrencyPrediction

Predict Cryptocurrency Price with Deep Learning

cs231n.github.io

Public facing notes page

Data-Science--Cheat-Sheet

Cheat Sheets

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

decagon

Graph convolutional neural network for multirelational link prediction

Deep-Learning-for-Medical-Applications

Deep Learning Papers on Medical Image Analysis

digital-horticulture

Disease_gene_prioritization_GCN

PGCN: Disease gene prioritization by disease and gene embedding through GCN

GEM

Lean-UX-Platform

The LEAN UX platform provides an innovative way of evaluating the User experience with the combined abilities of managing multi-modal, wide range of emotions, real-time synchronization, time spans based experience extraction, multi-device integration and powerful visualization.

medaCy

:hospital: Medical Text Mining and Information Extraction with spaCy

meshx-notes

Web System for Clinical Notes Information Extraction

ml_mda

Machine Learning for Medical Data Analysis

models

Models and examples built with TensorFlow

MRGC

Multi-view Robust Graph-based clustering for Cancer Subtype Identification

neural-network-from-scratch-1

A Neural Network implemented from scratch (using only numpy) in Python.

pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

py_entitymatching

pytorch-yolo-v3

A PyTorch implementation of the YOLO v3 object detection algorithm

read_docs

romdex

A novel approach for disease subtyping

spark

Apache Spark

Spectral-Clustering

Implementation of the algorithms described in "Ulrike von Luxburg, A Tutorial on Spectral Clustering"

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

testRepo33