Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Cross-platform, customizable ML solutions for live and streaming media.
- mediapipe
- c-plus-plus
- computer-vision
- deep-learning
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
- deep-learning
- document-parsing
- machine-learning
- nlp
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
- bloom
- deep-learning
- distributed-systems
- language-models
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
- mlops
- machine-learning
- data-science
- production-ready
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.
- machine-learning
- ml
- model-validation
- data-validation
AI Infra / AI Orchestration / AI Control Plane
Distributed Deep learning with Keras & Spark
MLBox is a powerful Automated Machine Learning python library.
- machine-learning
- auto-ml
- kaggle
- deep-learning
High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.
- flow
- rust
- rust-lang
- stream
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
- hpc
- workflow
- workflow-automation
- workflow-management
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning