A delightful machine learning tool that allows you to train/fit, test and use models without writing code.
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An open-source visual programming environment for battle-testing prompts to LLMs.
Toolset for black-box hyperparameter optimisation.
Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.
Distributed Asynchronous Hyperparameter Optimization in Python.
General Automated Machine Learning Framework.
A very simple wrapper for convenient hyperparameter optimization.
A service for deployment Apache Spark MLLib machine learning models as realtime, batch or reactive web services.
Platform for deploying your Machine Learning to production.
A framework for elegantly configuring complex applications.
"building applications with LLMs through composability".
General Machine Learning library using Numenta’s Cortical Learning Algorithm.
Library for hyperparameter optimization and black box optimization benchmarks.
Making large AI models cheaper, faster and more accessible.
Framework for distributed hyperparameter optimization.
Distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Framework for building applications with LLMs and Transformers (e.g. agents, semantic search, question-answering).
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Run LLM backends, APIs, frontends, and services with one command.
A curated list of Large Language Model.
Fundamentals of machine learning in python.