jinghaow Goto Github PK

applied_causal_inference_course

This course is an overview of applied causal inference.

citylearn

Official reinforcement learning environment for demand response and load shaping

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

deeplearningbook-chinese

Deep Learning Book Chinese Translation

english-writing

Enhance Your English Writing

gendis

Contains an implementation (sklearn API) of the algorithm proposed in "GENDIS: GEnetic DIscovery of Shapelets" and code to reproduce all experiments.

jericho-e-usage

The JERICHO-E-usage dataset including code for compilation. The dataset includes time series of useful energy consumption patterns for energy system modeling. The time series data covers 38 NUTS2 regions in germany and has an hourly resolution. The dataset distinguished between four sectors - the residential, the industrial, the commerce, and the mobility sectors. Useful energy types comprise space heating, warm water, process heating, space cooling, process cooling, mechanical energy, information and communication technology, and lighting.

latex

lstm_encoder_decoder

Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data

machine_learning_in_the_industry_4.0_seminar_ss2020.fau

Identifying a Trial Population for Clinical Studies on Diabetes Drug Testing with Neural Networks

mermaid

Generation of diagram and flowchart from text in a similar manner as markdown

minisom

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

mybooks

my books

neur2sp

Neur2SP: Neural Two-Stage Stochastic Programming

rul-net

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine

vedo

A python module for scientific analysis of 3D data