Hidden Markov Models for Python, implemented in Cython for speed and efficiency.
Yomu AI is an academic writing assistant for essays, papers, literature reviews and theses. It offers a document assistant for drafting sections, AI autocomplete, editing commands such as paraphrase and summarize, citation finding and formatting, a plagiarism checker, and chat with PDFs and images. Sources can be saved to a library and reused across documents. It is described as free to try with no credit card required.
SciSummary is an AI tool for researchers and students that summarizes and helps users understand scientific articles and research papers, and acts as an AI-powered reference and document manager. It supports bulk paper summarization, comparing papers, organizing a library with folders and tags, and chat messages. A free trial, a student plan and a pro plan are listed.
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.
A course by Andrej Karpathy on building neural networks from scratch in code, starting with backpropagation basics and building up to modern deep neural networks like GPT. Prerequisites are solid Python programming and intro-level math such as derivatives and gaussians.
Spinning Up is OpenAI's educational resource on deep reinforcement learning. Its documentation covers installation, included algorithms, running experiments, and an introduction to RL, along with algorithm pages for methods such as DDPG and PPO. The DDPG page describes an algorithm that concurrently learns a Q-function and a policy for continuous action spaces. The PPO page describes on-policy first-order methods, including PPO-Clip.
ELKI is an open source data mining software written in Java. It focuses on research in algorithms, emphasizing unsupervised methods in cluster analysis and outlier detection, and offers data index structures for performance and scalability. It is designed for researchers and students to extend.
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Yomu AI is an academic writing assistant for essays, papers, literature reviews and theses. It offers a document assistant for drafting sections, AI autocomplete, editing commands such as paraphrase and summarize, citation finding and formatting, a plagiarism checker, and chat with PDFs and images. Sources can be saved to a library and reused across documents. It is described as free to try with no credit card required.
SciSummary is an AI tool for researchers and students that summarizes and helps users understand scientific articles and research papers, and acts as an AI-powered reference and document manager. It supports bulk paper summarization, comparing papers, organizing a library with folders and tags, and chat messages. A free trial, a student plan and a pro plan are listed.
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.
A course by Andrej Karpathy on building neural networks from scratch in code, starting with backpropagation basics and building up to modern deep neural networks like GPT. Prerequisites are solid Python programming and intro-level math such as derivatives and gaussians.
Spinning Up is OpenAI's educational resource on deep reinforcement learning. Its documentation covers installation, included algorithms, running experiments, and an introduction to RL, along with algorithm pages for methods such as DDPG and PPO. The DDPG page describes an algorithm that concurrently learns a Q-function and a policy for continuous action spaces. The PPO page describes on-policy first-order methods, including PPO-Clip.
ELKI is an open source data mining software written in Java. It focuses on research in algorithms, emphasizing unsupervised methods in cluster analysis and outlier detection, and offers data index structures for performance and scalability. It is designed for researchers and students to extend.
