ASCII35's starred repositories

coding-interview-university

A complete computer science study plan to become a software engineer.

superset

Apache Superset is a Data Visualization and Data Exploration Platform

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google-research

Google Research

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nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Language:PythonLicense:MITStargazers:13908Issues:284Issues:2077

ml-visuals

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

ethminer

Ethereum miner with OpenCL, CUDA and stratum support

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Informer2020

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

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pytorch-forecasting

Time series forecasting with PyTorch

Language:PythonLicense:MITStargazers:3768Issues:40Issues:746

neural_prophet

NeuralProphet: A simple forecasting package

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PINNs

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

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shapash

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:2694Issues:37Issues:200

MEDIUM_NoteBook

Repository containing notebooks of my posts on Medium

Language:Jupyter NotebookLicense:MITStargazers:2056Issues:102Issues:50

multimodal

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

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tigramite

Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at

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innvestigate

A toolbox to iNNvestigate neural networks' predictions!

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Time-Series-Works-Conferences

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

TensorFlow-Time-Series-Examples

Time Series Prediction with tf.contrib.timeseries

pyEntropy

Entropy for Python

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alphasickle

多因子指数增强策略/多因子全流程实现

Applied-Machine-Learning-Explainability-Techniques

Applied Machine Learning Explainability Techniques, published by Packt

Language:Jupyter NotebookLicense:MITStargazers:235Issues:9Issues:1

GeoMLA

Machine Learning algorithms for spatial and spatiotemporal data

Language:RLicense:GPL-2.0Stargazers:203Issues:24Issues:2

BRITS

Code of NIPS18 Paper: BRITS: Bidirectional Recurrent Imputation for Time Series

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nco

netCDF Operators

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mfm_learner

我的多因子模型、量化投资沙盒

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anuvada

Interpretable Models for NLP using PyTorch

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TianChi_AIEarth

TianChi AIEarth Contest Solution

DualLearning

A dual learning toolkit developed by Microsoft Research

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LSTNet_Keras

my blog https://blog.csdn.net/qq_35649669/article/details/105586099

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