Popular GitHub Repositories for Debugging Rnns

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

An AI agent development platform with all-in-one visual tools, simplifying agent creation, debugging, and deployment like never before. Coze your way to AI Agent creation.

Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Debugging, monitoring and visualization for Python Machine Learning and Data Science

React app for inspecting, building and debugging with the Realtime API

Desktop app for prototyping and debugging LangGraph applications locally.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)

A reactive runtime for building durable AI agents

Implementations of CNNs, RNNs, GANs, etc

A database of SDKs, frameworks, libraries, and tools for creating, monitoring, debugging and deploying autonomous AI agents

The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy, pytorch, jax, tensorflow, keras, fastai.

Visualization and debugging tool for LangChain workflows

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Simple baselines and RNNs for predicting human motion in tensorflow. Presented at CVPR 17.

Enable any LLM (e.g. Claude) to interactively debug any language for you via MCP and a VS Code Extension

The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud.

The collaborative real-time open-source machine learning devtool and training suite: Experiment execution, tracking, and debugging. With server and project management tools.

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press