Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

syftr is an agent optimizer that helps you find the best agentic workflows for your budget.

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.

Sequential model-based optimization with a `scipy.optimize` interface

AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI

sharpDARTS: Faster and More Accurate Differentiable Architecture Search

We share in this repository some codes and data used during our research about glass property prediction and the design of new glasses.

Hyperparameter selection on machine learning models using Particle Swarm Optimization

Efficient AutoRL script for any framework

Sentiment analysis for amazon product reviews using NLTK, Scikit-Learn, and Keras. Using hyperparameter search and LSTM, our best model achieves ~96% accuracy.

ray project 中文文档

CS5228 Kaggle Inclass Competition: Predicting if Income > 50K

Selected Paper from the AI-CyberSec 2021 Workshop in the 41st SGAI International Conference on Artificial Intelligence (MDPI Journal Electronics)

MLOps Python library/platform for tracking machine learning projects