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General Machine Learning library using Numenta’s Cortical Learning Algorithm.
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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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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.
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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.
Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING].
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Rails-like inflection library for Clojure and ClojureScript.
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AI-native database built for LLM applications, providing incredibly fast vector and full-text search.
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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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Autograd and XLA for high-performance machine learning research.
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A python library for doing approximate and phonetic matching of strings.
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A project to make it easier to use large external knowledge bases with LLMs.
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Chinese Words Segmentation Utilities.
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Chinese Words Segmentation Utilities.
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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.