Popular GitHub Repositories for Continuous Profiling

An open-source runtime for composable workflows. Great for AI agents and CI/CD.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

?? CML - Continuous Machine Learning | CI/CD for ML

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

TorchCFM: a Conditional Flow Matching library

Open-Source Large Vocabulary Continuous Speech Recognition Engine

MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Learning Continuous Image Representation with Local Implicit Image Function, in CVPR 2021 (Oral)

Automatically find issues in image datasets and practice data-centric computer vision.

Profiling and inspecting memory in pytorch

Closed-form Continuous-time Neural Networks

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space.

The Fastest Deep Reinforcement Learning Library

A Python API for accessing resources and configuring Hudson & Jenkins continuous-integration servers

? Run Claude Code in a continuous loop, autonomously creating PRs, waiting for checks, and merging