Machine Learning

Docspell organizes scanned documents, email attachments, and other files in a personal document management system.

Land Lines uses gestures to find matching Google Earth satellite images, turning drawn lines into visual compositions.

This curated AI and machine learning guide organizes over 228 learning resources across 30 sections.

Weka 3 provides open source machine learning and data mining software written in Java.

The ICML site provides information about the International Conference on Machine Learning in Lille.

Data Science IPython Notebooks collects notebooks about data science, including TensorFlow deep learning.

Vaex provides out-of-core DataFrames for Python to explore and visualize large tabular datasets, with support for machine learning workflows.

Ultralytics supports detection, segmentation, image classification, pose estimation, and tracking across YOLO model versions.

Ask Vane questions and get responses through its artificial intelligence answering engine.

Treat supplies Ruby developers with a framework for natural language processing.

BigML provides a platform for creating machine learning models and working with data.

Build dialogue systems and chatbots with DeepPavlov, an open-source NLP framework using PyTorch and transformer models.

Deploy a ML inference service on a budget in less than 10 lines of code.

The MegEngine framework supports deep learning and automatic differentiation, according to its repository description.

Use Aeromancy to build reproducible machine learning workflows and projects.

Notey combines automated analysis with editorial research to help users discover blogs and organize web content.

Generated Photos offers AI-generated faces and full-body people images, with collections to browse and generators that create new images from set parameters.

This GitHub Blog article explains the architecture of today’s LLM applications and ways to begin building one.

N2D2 provides an open source CAD framework for deep neural network simulation and application building.

This book introduces the central ideas behind deep learning for newcomers and readers already experienced in machine learning.

Accord.NET combines machine learning with audio and image processing libraries in a C# framework.

Codeaid provides coding assessments for AI and machine-learning engineering roles, with online tests for evaluating candidates.

This GitHub list collects papers, repositories and other data about anime and manga research.

Machine Learning Systems is a two-volume textbook about how machine learning systems are built, covering the engineering behind AI.