Awesome AI Tools
Section: Developer tools · Open-source tool for ML observability that runs in your notebook environment, by Arize. Monitor and fine-tune LLM, CV, and tabular models.
SlowScore 67
Entry
Phoenix
Appears in 6 awesome lists
Phoenix from the team at Arize is an open source library that helps you auto instrument, trace, evaluate and observe AI agents and LLM systems github | comparison X
Found in these lists
Awesome Machine Learning
Section: C++ · Uncover insights, surface problems, monitor and fine tune your generative LLM, CV and tabular models.
FreshScore 93
Awesome MLOps
Section: Visual Analysis and Debugging · MLOps in a Notebook for troubleshooting and fine-tuning generative LLM, CV, and tabular models.
FreshScore 80
Indie Hacker Tools Plus
Section: LLM 评测与治理 (LLM Evaluation & Harness) · 开源可观测性。支持 RAG 可视化、嵌入空间分析及 Agent 追踪。
FreshScore 86
Awesome AI Agents: Tools, Resources, and Projects
Section: Repositories · Phoenix from the team at Arize is an open source library that helps you auto instrument, trace, evaluate and observe AI agents and LLM systems github | comparison X
SlowScore 68
Awesome Generative AI
Section: Developer tools · Open-source tool for ML observability that runs in your notebook environment, by Arize. Monitor and fine tune LLM, CV and tabular models.
FreshScore 90
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Opik
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Netron
Visualizer for deep learning and machine learning models (no Python code, but visualizes models from most Python Deep Learning frameworks).
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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. [Apache2]
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CatBoost
General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
In 10 listsDetails
Langfuse
LLM engineering platform for model tracing, prompt management, and application evaluation. Langfuse helps teams collaboratively debug, analyze, and iterate on their LLM applications such as chatbots or AI agents. (Demo, Source Code, Clients) MIT Docker
In 10 listsDetails
Caffe
is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.
In 10 listsDetails