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Machine learning for NeuroImaging in Python
The main features of nilearn/nilearn are: General Machine Learning, Neuroscience Programming.
Projects with overlapping indexed features include: morvanzhou/tutorials — This repository is a comprehensive collection of instructional guides and practical examples for Python development,… activeloopai/hub — Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and… aimhubio/aim — Aim is an open-source platform for logging, visualizing, and comparing machine learning training runs and LLM traces.… ajtulloch/haskell-ml — Haskell implementations of various ML algorithms. aksnzhy/xlearn — High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization… aces/brainbrowser — BrainBrowser is a JavaScript library allowing for web-based, 2D and 3D visualization of neurological data. It consists…
This repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad
Hub is a multimodal AI data lake and vector database designed for storing and querying embeddings, text, audio, and images. It functions as a dataset version control system and a machine learning data streaming engine to support large-scale model training. The system utilizes a serverless PostgreSQL vector store to index high-dimensional embeddings for semantic search. It provides a visual interface for inspecting multimodal datasets and viewing annotations such as bounding boxes and masks. The platform handles cloud-agnostic storage synchronization and implements lazy, compressed data strea
Aim is an open-source platform for logging, visualizing, and comparing machine learning training runs and LLM traces. It provides a remote tracking server and a comparison UI, functioning as an ML experiment tracker, AI workflow logger, and LLM trace recorder that captures prompts, generations, and tool calls from AI applications. The platform distinguishes itself through a run-based data model with local SQLite storage, real-time metric streaming, and a plugin-based explorer system that supports specialized visual analysis of metrics, images, audio, and text. It offers a Python SDK with cont
BrainBrowser is a JavaScript library allowing for web-based, 2D and 3D visualization of neurological data. It consists of the Surface Viewer, a real-time 3D rendering tool for visualizing surface data, and the Volume Viewer, a slice-by-slice volumetric data analysis tool.