Directory
Models and machine learning covers model hubs, research papers, training guides and evaluation tools. The topic mixes practical resources with reference material, so you will find repositories that host downloadable models next to sites that explain how a technique works. Some entries are collections of papers or benchmarks, and others are tutorials that walk through fine-tuning or deployment. It pays to compare the model licence, the training data, the hardware needed and the date of the last update. The field moves quickly, so verify version notes on the source before you build on anything listed here.
Feature Stores for ML is a global community of data science professionals, researchers, and engineers focused on feature stores for machine learning pipelines. It creates educational content about feature stores and the surrounding data and AI ecosystem, hosts monthly industry meetups, and provides resources including blog posts, videos, benchmarks, and an MLOps dictionary.
Set of tools for creating and testing machine learning features, with a scikit-learn compatible API.
Python library for automated feature engineering.
FedML is a unified and scalable open-source machine learning library for large-scale distributed training, model serving, and federated learning. It includes FEDML Launch, a cross-cloud scheduler for running AI workloads on GPU clouds or on-premise clusters, and forms the foundation of the TensorOpera AI generative AI platform.
fenn is a Python framework for building machine learning and deep learning workflows and LLM agents. It provides prebuilt trainers, agent templates, logging, and configuration management, with YAML configuration parsed and injected into the entrypoint with CLI override support. It is released under the MIT license.
Fiber is a Python-based distributed computing library for modern computer clusters. It provides the same API as Python's standard multiprocessing library, uses Nanomsg for communication, and allows dynamic allocation of CPU, memory, and GPU resources. Installation uses pip install fiber.
Fiddler is an AI control plane platform for enterprise AI agent deployments. It offers evaluation, monitoring, policy enforcement, governance, and cost efficiency functionality for enterprise AI systems. The platform supports use cases across government, financial services, healthcare, and insurance sectors.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A highly-modular C++ machine learning library for embedded electronics and robotics.
A Scala library for constructing probabilistic models.
Figure is the first-of-its-kind AI robotics company bringing a general purpose humanoid to life.
FigureLabs is an AI scientific figure generator that creates illustrations, flowcharts and plots. It accepts text, sketches, lab photos, spreadsheets, PDFs or reference figures as input, then allows editing of text, colors, backgrounds and resolution on a canvas. Figures can be exported as editable PPTX or SVG, or as PNG and JPG images.
Secure zero-knowledge encrypted file sharing (AES-256-GCM in-browser). No account required, MIT licensed, self-hostable, optional link expiry.
Using AI, FinChat generates answers to questions about public companies and investors.
finetuning-scheduler is a PyTorch Lightning extension for foundation model experimentation with flexible fine-tuning schedules. It supports explicit or regex-based parameter selection and implicit schedules for initial model exploration, plus automatic restoration of best per-phase checkpoints using early-stopping criteria for each phase. An experimental API, FTSController, brings the same schedules to a plain PyTorch training loop.
Flama is a production framework for predictive and generative AI. It enables serving any machine learning model as an API with a single line of code, and offers OpenAI, Anthropic, and Ollama-compatible endpoints, a built-in chat user interface, and native MCP support.
FLAML is a lightweight Python library from Microsoft for automating machine learning and AI operations. It performs model selection and hyperparameter optimization under resource constraints, including tuning foundation model inference hyperparameters. It requires Python 3.10 or later, is installable via pip, and can be used as a scikit-learn style estimator.
Flare is a Clojure library for building dynamic neural network graphs, described as similar to PyTorch and DynNet. It supports tensor operations, LSTM cells, one-dimensional CNNs and fixed embeddings, and uses Neanderthal as its tensor backend. The project states it is mostly for learning purposes.
FlexGen is a software project that enables running large language models on a single GPU. It focuses on throughput-oriented scenarios, offering an approach to efficient inference. The project is available on GitHub as FMInference/FlexLLMGen.
FlexML is an AutoML library for Python that assists in building machine learning models by automating model selection and hyperparameter tuning. It supports regression and classification tasks and offers quick and wide experiment modes for choosing how many models to train.
Flight Fare Prediction is a GitHub repository that implements a machine learning project for predicting flight fares. The repository includes documentation such as a problem statement and topics related to the prediction task.
Floode provides machine-learning models, research, training resources, or evaluation tools.
Friendly Federated Learning Framework.
Drag & drop UI to build your customized LLM flow using LangchainJS.
