vincentliuheyang

AI-Expert-Roadmap

Roadmap to becoming an Artificial Intelligence Expert in 2022

stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

autograd

Efficiently computes derivatives of numpy code.

Elastic-Federated-Learning-Solution

website

Source for https://fullstackdeeplearning.com

ncps

PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models

GraphScope

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

CfC

Closed-form Continuous-time Neural Networks

tsai

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

darts

A python library for user-friendly forecasting and anomaly detection on time series.

rayfed

A multiple parties joint, distributed execution engine based on Ray, to help build your own federated learning frameworks in minutes.

ToMe

A method to increase the speed and lower the memory footprint of existing vision transformers.

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

ant-xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

tf-encrypted

A Framework for Encrypted Machine Learning in TensorFlow

tods

TODS: An Automated Time-series Outlier Detection System

nibabel

Python package to access a cacophony of neuro-imaging file formats

codon

A high-performance, zero-overhead, extensible Python compiler using LLVM

chardet

Python character encoding detector

cmu_15-445

数据库课程项目 CMU 15-445 (Fall 2019)

hmm

An implementation of the Viterbi Algorithm for training Hidden Markov models. This repo accompanies the video found here: https://www.youtube.com/watch?v=kqSzLo9fenk

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

ml-visuals

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

optbinning

Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual explanations.

chaosblade

An easy to use and powerful chaos engineering experiment toolkit.（阿里巴巴开源的一款简单易用、功能强大的混沌实验注入工具）

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

xgboost_ray

Distributed XGBoost on Ray

mars

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

notes-on-dirichlet-processes

:game_die: Notes explaining Dirichlet Processes, HDPs, and Latent Dirichlet Allocation

PyTorch-BigGraph

Generate embeddings from large-scale graph-structured data.