This GitHub repository hosts an open solution for the Santander Value Prediction Challenge. It outlines the project's goals, includes a disclaimer, provides guidance for getting started, and links to related competition resources, while accepting community contributions.
A visualisation of major large-language models ranked by performance using the MMLU benchmark, which consists of 16,000 multiple-choice questions across 57 academic subjects. It also presents selected lawsuits filed against AI companies and notes that MMLU has some critiques.
Accord.NET is a .NET machine learning framework combined with audio and image processing libraries written in C#. It covers classification, regression, clustering, distributions, hypothesis tests and kernel methods, with imaging and signal processing components. The framework is intended for building computer vision, audition, signal processing and statistics applications, including commercial use. It offers sample applications, documentation and a wiki.
An index page from LabLab for discovering AI technologies and related topics. Each technology page is described as offering tutorials, upcoming hackathons, frameworks and boilerplates. Listed technologies include GPT-4, ChatGPT, BERT, AI21 Labs, Anthropic, AWS, Cohere, Hugging Face and DeepSeek.
gotoHuman is a platform for supervising AI agents, letting workflows request human review of critical steps. Reviewers approve and edit AI-generated content in an Agent Inbox, with email and Slack notifications, and completed reviews return to the workflow via webhook. Review types are configured in a no-code editor and can capture text, images, markdown and JSON.
Magenta is an open source research project exploring the role of machine learning as a tool in the creative process, focused on art and music. It includes Magenta Studio, a collection of music plugins for Ableton Live, and Magenta RealTime 2, an open model and real-time neural synthesis engine.
Flux is a machine learning library built as a pure-Julia stack, offering lightweight abstractions over Julia's native GPU and automatic differentiation support. It is compiled and eager, and existing Julia libraries can be incorporated into Flux models. Its ecosystem includes probabilistic programming, graph neural networks, computer vision and natural language processing packages, and it is maintained by a community team.
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A visualisation of major large-language models ranked by performance using the MMLU benchmark, which consists of 16,000 multiple-choice questions across 57 academic subjects. It also presents selected lawsuits filed against AI companies and notes that MMLU has some critiques.
Accord.NET is a .NET machine learning framework combined with audio and image processing libraries written in C#. It covers classification, regression, clustering, distributions, hypothesis tests and kernel methods, with imaging and signal processing components. The framework is intended for building computer vision, audition, signal processing and statistics applications, including commercial use. It offers sample applications, documentation and a wiki.
An index page from LabLab for discovering AI technologies and related topics. Each technology page is described as offering tutorials, upcoming hackathons, frameworks and boilerplates. Listed technologies include GPT-4, ChatGPT, BERT, AI21 Labs, Anthropic, AWS, Cohere, Hugging Face and DeepSeek.
gotoHuman is a platform for supervising AI agents, letting workflows request human review of critical steps. Reviewers approve and edit AI-generated content in an Agent Inbox, with email and Slack notifications, and completed reviews return to the workflow via webhook. Review types are configured in a no-code editor and can capture text, images, markdown and JSON.
Magenta is an open source research project exploring the role of machine learning as a tool in the creative process, focused on art and music. It includes Magenta Studio, a collection of music plugins for Ableton Live, and Magenta RealTime 2, an open model and real-time neural synthesis engine.
Flux is a machine learning library built as a pure-Julia stack, offering lightweight abstractions over Julia's native GPU and automatic differentiation support. It is compiled and eager, and existing Julia libraries can be incorporated into Flux models. Its ecosystem includes probabilistic programming, graph neural networks, computer vision and natural language processing packages, and it is maintained by a community team.
