nathanielkang Goto Github PK

239as-rl-proj

amortization

Python library for calculating amortizations and generating amortization schedules

cdsml

Classification of drug response using machine learning

consdeepsignaling

Construct a Biological Meaningful Deep Learning Model, Also With Global Interpreation

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

data_science

deep-q-networks

Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51

deepred

A PyTorch implementation of DeepRed

deeprlbreakout

Replicating DQN papers by DeepMind for Breakout game

disentangled-attribution-curves

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

dmol-book

Deep learning for molecules and materials book

dueling_network_architectures

Implementation of Dueling Network Architectures for Deep Reinforcement Learning paper with Pytorch

ee227c.github.io

EE227C (Spring 2018) Course page

fedshare

PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.

flower

Flower: A Friendly Federated Learning Framework

gatas

Graph Representation Learning Network via Adaptive Sampling

gem

graphdrp

gratransdrp

gsp-py

GSP (Generalized Sequence Pattern) algorithm in Python

imbalanced-regression

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

jodie

A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

machine-learning-for-time-series-with-python

Machine Learning for Time-Series with Python.Published by Packt

mad-from-scratch

Machine learning, artificial intelligence, and data analytics built from scratch.

matsuolab-edu-dl4us

mead-tutorials

Tutorial on using MEAD

midas_pro

Python version of Mixed Data Sampling (MIDAS) regression (allow for multivariate MIDAS) :golf:

moa

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

moli

MOLI: Multi-Omics Late Integration with deep neural networks for drug response prediction