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Framework for distributed hyperparameter optimization.
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Making large AI models cheaper, faster and more accessible.
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"building applications with LLMs through composability".
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A framework for elegantly configuring complex applications.
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Platform for deploying your Machine Learning to production.
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A service for deployment Apache Spark MLLib machine learning models as realtime, batch or reactive web services.
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A very simple wrapper for convenient hyperparameter optimization.
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General Automated Machine Learning Framework.
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Distributed Asynchronous Hyperparameter Optimization in Python.
Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.
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Toolset for black-box hyperparameter optimisation.
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An open-source visual programming environment for battle-testing prompts to LLMs.
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A delightful machine learning tool that allows you to train/fit, test and use models without writing code.
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Julia-language backend combined with the Jupyter interactive environment.
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Framework to connect a flow of ML models by applying graph theory.
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A toolkit to help understand models and enable responsible machine learning.
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Notebooks and code for the book "Introduction to Machine Learning with Python".
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jd-gui is a GitHub repository or organization with source code, releases, documentation, or project resources.
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Chinese Words Segmentation Utilities.
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Chinese Words Segmentation Utilities.
Code for interactive simulacra of human behavior [[arxiv]](https://arxiv.org/abs/2304.03442).
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Machine learning toolkit with classification and clustering for Node.js; supports visualization (see visualml.io).
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Jupyter notebook is a web-based notebook environment for interactive computing.
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Code for the Kaggle acquire valued shoppers challenge.