Beer glass classifier created with Synaptic.
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Fundamentals of machine learning in python.
A curated list of Large Language Model.
Run LLM backends, APIs, frontends, and services with one command.
Framework for building applications with LLMs and Transformers (e.g. agents, semantic search, question-answering).
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
Distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Framework for distributed hyperparameter optimization.
Library for hyperparameter optimization and black box optimization benchmarks.
General Machine Learning library using Numenta’s Cortical Learning Algorithm.
"building applications with LLMs through composability".
A framework for elegantly configuring complex applications.
Platform for deploying your Machine Learning to production.
A very simple wrapper for convenient hyperparameter optimization.
General Automated Machine Learning Framework.
Distributed Asynchronous Hyperparameter Optimization in Python.
Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.
Toolset for black-box hyperparameter optimisation.
An open-source visual programming environment for battle-testing prompts to LLMs.
Julia-language backend combined with the Jupyter interactive environment.
Creates or edits images with generative models and visual controls.
Rails-like inflection library for Clojure and ClojureScript.
AI-native database built for LLM applications, providing incredibly fast vector and full-text search.
Notebooks and code for the book "Introduction to Machine Learning with Python".