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Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Pytorch Handbook ⭐ 18,594

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友

Amazon Sagemaker Examples ⭐ 9,221

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Flaml ⭐ 3,500

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Scikit Learn Videos ⭐ 3,180

Jupyter notebooks from the scikit-learn video series

Lazypredict ⭐ 2,275

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

Mlj.jl ⭐ 1,690

A Julia machine learning framework

Machine Learning in R

Advisor ⭐ 1,202

Open-source implementation of Google Vizier for hyper parameters tuning

Vizier ⭐ 1,142

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

Hyperband ⭐ 515

Tuning hyperparams fast with Hyperband

Sharplearning ⭐ 372

Machine learning for C# .Net

Adaptnlp ⭐ 371

An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

Sentimentanalysis ⭐ 260

Sentiment analysis neural network trained by fine-tuning BERT, ALBERT, or DistilBERT on the Stanford Sentiment Treebank.

A universal flight control tuning framework

Dynamic Training Bench ⭐ 214

Simplify the training and tuning of Tensorflow models

Adatune ⭐ 144

Gradient based Hyperparameter Tuning library in PyTorch

Mxnet Finetuner ⭐ 99

An all-in-one Deep Learning toolkit for image classification to fine-tuning pretrained models using MXNet.

Awslambdaface ⭐ 96

Perform deep neural network based face detection and recognition in the cloud (via AWS lambda) with zero model configuration or tuning.

Lstm_chem ⭐ 91

Implementation of the paper - Generative Recurrent Networks for De Novo Drug Design.

Dataminingnotesandpractice ⭐ 88

记录我学习数据挖掘过程的笔记和见到的奇技，持续更新～

Hyperparameter tuning for machine learning models using a distributed genetic algorithm

[ACL 19] Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction

Autogbt Alt ⭐ 73

An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.

Ml Agents Hyperparams ⭐ 64

Automated Hyperparameter Search for Unity ML-Agents

Apache Spark (Scala, PySpark, SparkR) Code, Tricks, and References

Vae_captioning ⭐ 52

Implementation of Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space

Deep_traffic ⭐ 49

MIT DeepTraffic top 2% solution (75.01 mph) 🚗.

Mlr3tuning ⭐ 46

Hyperparameter optimization package of the mlr3 ecosystem

Sparkxgb ⭐ 40

R interface for XGBoost on Spark

Ck Crowdtuning ⭐ 34

Collective Knowledge crowd-tuning extension to let users crowdsource their experiments (using portable Collective Knowledge workflows) such as performance benchmarking, auto tuning and machine learning across diverse platforms with Linux, Windows, MacOS and Android provided by volunteers. Demo of DNN crowd-benchmarking and crowd-tuning:

Mlrhyperopt ⭐ 31

Easy Hyper Parameter Optimization with mlr and mlrMBO.

Few-shot learning framework for opinion summarization published at EMNLP 2020.

Convolutional Neural Network based on Hierarchical Category Structure for Multi-label Short Text Categorization

Paramhelpers ⭐ 25

Helpers for parameters in black-box optimization, tuning and machine learning.

Flexible Bayesian Optimization in R

Apollo: Online Machine Learning for Performance Portability

Gbm Tune ⭐ 21

Tuning GBMs (hyperparameter tuning) and impact on out-of-sample predictions

Mlr3hyperband ⭐ 17

Successive Halving and Hyperband in the mlr3 ecosystem

This repository contains demo notebooks (sample code) for the AutoMLx (automated machine learning and explainability) package from Oracle Labs.

Kanji testing web app leveraging ML

Hypertune ⭐ 12

Hyperparameter tuning using Particle Swarm Optimization and parallel computation which outperforms current approaches. V0.1 Beta

User2020 ⭐ 11

Material for the useR2020 tutorial

Neural Networks ⭐ 10

A basic ANN repository for understanding Neural networks without any black box approach

Mlr3tuningspaces ⭐ 10

Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem

Machinelearning Datascience ⭐ 9

Complete Machine Learning and Data Science: Zero to Mastery

Py Hyperpy ⭐ 8

HyperaPy: An automatic hyperparameter optimization framework ⚡🚀

Kaggle Predict Future Sales ⭐ 7

Kaggle's Predict Future Sales competition project (TOP 15 solution as of March 2020)

Optimization algorithms for Machine Learning problems like Hyperparameter tuning and Ensembling.

Kaggle Dsg Qualification ⭐ 6

Data Science Game 2016 Qualification Round Solution

Semi-automated machine learning pipelines

Machinelearning ⭐ 6

An R Package for Estimating Time-Varying Graphical Models

Fine Tuning Bert For Text Classification ⭐ 5

Machine Learning Hyper-parameter Tuning processes

H2o Tutorial ⭐ 5

H2O Tuning and Ensembling Tutorial for R

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