bit-whacker's repositories
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
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.
Deep-Learning-for-Medical-Applications
Deep Learning Papers on Medical Image Analysis
Disease_gene_prioritization_GCN
PGCN: Disease gene prioritization by disease and gene embedding through GCN
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.
meshx-notes
Web System for Clinical Notes Information Extraction
neural-network-from-scratch-1
A Neural Network implemented from scratch (using only numpy) in Python.
pytorch-yolo-v3
A PyTorch implementation of the YOLO v3 object detection algorithm
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