Directory
Published directory entries matching your search.
Detecto is a Python package for building computer vision and object detection models with PyTorch. It supports inference on still images and videos, transfer learning on custom datasets, and serialization of models to files, and is distributed under an MIT license.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for experimentation and research with probabilistic models, from hierarchical models on small data sets to deep probabilistic models on large data sets. It fuses Bayesian statistics and machine learning, deep learning, and probabilistic programming, and is built on TensorFlow.
Python package which helps to debug machine learning classifiers and explain their predictions.
EncodeDna.com is a developer resource offering online tools, tutorials, guides and articles on web development topics such as Python, Node.js, JavaScript, Angular, CSS and color theory. Its browser-based tools include an image viewer, HTML minifier, image cropper, color palette generator, JSON validator and notepad. Articles are described as new regularly and free for ever.
EvalML is an AutoML library written in Python that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions. It includes data quality checks, cross-validation, preprocessing, feature engineering, feature selection, and model understanding tools. Install from PyPI or conda-forge.
A fast Evolution Strategy implementation in Python.
Fairlearn is a Python package hosted on a GitHub repository maintained by the Fairlearn project, designed to assess and improve the fairness of machine learning models. The repository includes documentation covering fairness definitions and a getting started guide for the tool.
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.
A free, continuously evolving downloadable book collecting community knowledge on 2D game development. It does not teach a specific tool, instead offering tips and tricks applied to any engine or built from scratch. Editions are available in pseudocode, Python, C++, JavaScript, Lua and Rust; some versions require thorough revision.
An open source Python library for drift detection in machine learning systems.
futurecoder is a free and open-source interactive course that teaches Python programming from scratch to complete beginners. Users run code in the provided editor or shell and answer questions to advance. Features include three debuggers for visualizing execution, beginner-friendly error messages, Parsons problems, and solution breadcrumbs.
Genepy is a website offering interactive Python exercises, including basics, functions, comparisons and word counting. It provides immediate feedback from its corrector and supports individual and team leaderboards. A command line interface is available for users who prefer not to use the web editor.
Fundamentals of machine learning in python.
WorldWide Telescope is a suite of free and open source software and data sets that combine to create scientific visualizations and stories. Its ecosystem includes a Windows application, an interactive web app, and toolkits for Python and TypeScript/JavaScript.
Hyperopt is an open-source Python library available on GitHub, designed to provide distributed asynchronous hyperparameter optimization functionality for tuning machine learning models in development workflows, production environments, as well as research settings.
An open source, MIT-licensed Python library imported as imblearn that relies on scikit-learn. It provides tools for classification with imbalanced classes. The documentation includes installation guides, a user guide, an API reference and a gallery of examples.
Kubeflow Katib is a Kubernetes-native project for automated machine learning (AutoML). It supports hyperparameter tuning, early stopping and neural architecture search, and is agnostic to machine learning frameworks, natively supporting frameworks such as TensorFlow, PyTorch and XGBoost. Training jobs can use any Kubernetes Custom Resources, with out-of-box support for Kubeflow Training Operator, Argo Workflows and Tekton Pipelines. A Python SDK simplifies creating tuning jobs.
A beginner-friendly guide on using Keras to implement a simple neural network in Python. It walks through MNIST handwritten digit classification, covering setup, data preparation, building the model, compiling, training, testing and using the model. It is intended for complete beginners to Keras who have a basic background knowledge of neural networks.
A personal collection of solutions to LeetCode problems written in C++23, Java, Python, MySQL, and TypeScript. The site aims to provide readable code with consistent style. Solutions can be found by searching by number or title. The repository does not accept pull requests, though forking is allowed.
LIBSVM is an integrated software library for support vector classification, regression and distribution estimation. It provides a simple interface for linking with other programs and includes multi-class classification, cross-validation and probability estimates. Interfaces exist for Python, R, MATLAB and other languages.
LightFM is a Python implementation of recommendation algorithms for implicit and explicit feedback. It allows item and user metadata to be incorporated into matrix factorization algorithms, representing users and items as sums of latent feature representations. Installation is available from PyPI, and a Docker setup is provided for running examples and tests.
LightlySSL is a Python computer vision framework for self-supervised learning on images, written in a PyTorch-like style. It exposes low-level building blocks such as loss functions and model heads, supports custom backbone models for self-supervised pre-training, and supports distributed training using PyTorch Lightning. Sample code covers models including MoCo, SimCLR, BYOL and DINO.
Lobe is a free tool for Mac and PC that helps users train machine learning models and ship them to any platform. The GitHub organization hosts starter projects for iOS and web, a Python toolset for working with Lobe models, and tools for creating image-based datasets. The team states the Lobe desktop application is no longer under development.
Lucas Chess is an open source chess program developed with Python and PySide2 for training, playing and competing on a PC. It includes 57 prepared engines with levels from 0 to 3600 elo, and other UCI engines can be added. The program offers trainings, tournaments and PGN database tools.
