Showing 63 open source projects for "data visualization, research"

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  • 1
    Book2_Beauty-of-Data-Visualization

    Book2_Beauty-of-Data-Visualization

    Machine Learning, Criticism and Correction

    Book2_Beauty-of-Data-Visualization is an open educational project that teaches the principles and techniques of effective data visualization using Python and modern plotting libraries. The repository focuses on both the technical and aesthetic aspects of visual analytics, helping learners understand how to communicate data clearly and persuasively. It includes practical examples that demonstrate how different chart types reveal patterns, trends, and distributions in real datasets. ...
    Downloads: 1 This Week
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  • 2
    Scientific Visualization

    Scientific Visualization

    An open access book on scientific visualization using python

    The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling.
    Downloads: 0 This Week
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  • 3
    Local Deep Research

    Local Deep Research

    95% on SimpleQA (e.g. Qwen3.6-27B on a 3090)

    Local Deep Research is an open-source AI-powered research assistant designed to perform deep, iterative investigations by combining large language models with multi-source search capabilities. It runs locally, giving users full control over their data, privacy, and infrastructure while supporting both local and cloud-based LLMs. The system breaks down complex queries into smaller steps, performs parallel searches across web and academic sources, and generates structured, citation-backed reports. ...
    Downloads: 1 This Week
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  • 4
    Megatron-LM

    Megatron-LM

    Ongoing research training transformer models at scale

    ...The repository provides both a reference training implementation and Megatron Core, a composable library of high-performance building blocks for custom large-model pipelines. It supports advanced parallelism strategies including tensor, pipeline, data, expert, and context parallelism, enabling training across massive multi-GPU and multi-node clusters. The framework includes mixed-precision training options such as FP16, BF16, FP8, and FP4 to maximize performance and memory efficiency on modern hardware. Megatron-LM is widely used in research and industry for pretraining GPT-, BERT-, T5-, and multimodal-style models, with tooling for checkpoint conversion and interoperability with Hugging Face. ...
    Downloads: 14 This Week
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    Growth Lab

    Growth Lab

    An end-to-end growth tool that understands the product

    ...The project currently includes workflows for SEO page growth and Xiaohongshu content research, creation, compliance checks, and review. Product data and operational memory stay in the user's own workspace rather than a proprietary hosted format.
    Downloads: 1 This Week
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  • 6
    nanoGPT

    nanoGPT

    The simplest, fastest repository for training/finetuning models

    NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare...
    Downloads: 9 This Week
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  • 7
    Book1_Python-For-Beginners

    Book1_Python-For-Beginners

    The Iris Book: Addition, Subtraction, Multiplication, and Division

    ...It integrates visual aids and annotated code examples to help learners understand not just how Python works but why certain patterns are used. The material is structured to support self-paced learning, making it suitable for students, career switchers, and hobbyists. Because the book is part of a larger data science pathway, it also prepares readers for later work in visualization and machine learning. Overall, it serves as an accessible on-ramp into Python within a broader analytical learning journey.
    Downloads: 1 This Week
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  • 8
    AI Researcher

    AI Researcher

    An autonomous AI researcher

    ...The system emphasizes modularity, so teams can swap in new reasoning modules, data retrieval strategies, or domain knowledge bases depending on the research topic. Through self-supervised feedback loops, agents adjust their strategies based on prior outcomes, improving both the quality and relevance of results over time.
    Downloads: 0 This Week
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  • 9
    ThinkStats2

    ThinkStats2

    Text and supporting code for Think Stats, 2nd Edition

    ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic...
    Downloads: 0 This Week
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  • 10
    xrayutilities

    xrayutilities

    a package with useful scripts for X-ray diffraction physicists

    xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More...
    Downloads: 11 This Week
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  • 11

    openSkyMatch

    Matches OpenScience Observatories images with astronomical catalogs

    openSkyMatch is a collection of Linux shell and Python scripts designed for the OpenScience Observatories program. It automates the identification and matching of detected celestial objects in locally captured FITS images with entries in large-scale sky catalogs, notably Pan-STARRS1 DR2 (II/389/ps1_dr2). The toolkit supports data preprocessing, coordinate correlation, and catalog-based validation of astronomical detections. All tools are open-source and optimized for reproducibility and...
    Downloads: 0 This Week
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  • 12
    ACORBA

    ACORBA

    Automated approach to measure root tip angles of Arabidopsis thaliana

    Gravitropic response is studied in most of the laboratories working with Arabidopsis thaliana, for example, to detect new phenotypes in mutants. However, manual analysis of images and microscopy data are known to be subjected to human bias. This is particularly the case for manual measurements of root bending as the angle is set subjectively. In this context, it is essential to develop and use automated or semi-automated image analysis to produce faster, reproducible, and unbiased data. In...
    Downloads: 2 This Week
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  • 13
    Br-Gogo is a Brazilian open-source version of the Gogo Board project. Developed by CTI, a Brazilian research center. **<div class="sf-root" data-id="250926" data-badge="oss-users-love-us-white" style="width:125px"> <a href="https://sourceforge.net/projects/br-gogo/" target="_blank">Br-Gogo</a> </div>**
    Downloads: 0 This Week
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  • 14
    DIG

    DIG

    A library for graph deep learning research

    ...It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms.
    Downloads: 0 This Week
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  • 15
    HomeworkHelper

    HomeworkHelper

    Homework Helper: Organize tasks, meet deadlines. Ideal for ADHD

    Homework Helper is a comprehensive and user-friendly application designed to assist students in effectively managing their homework and assignments. It provides a convenient and organized platform to keep track of upcoming tasks, due dates, subjects, and associated details. Developed with a focus on simplicity and usability, Homework Helper aims to support students, including those with ADHD or individuals struggling with task management, in staying organized and achieving academic success....
    Downloads: 0 This Week
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  • 16
    AllenNLP

    AllenNLP

    An open-source NLP research library, built on PyTorch

    AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional...
    Downloads: 2 This Week
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  • 17
    ety

    ety

    A Python module to discover the etymology of words

    ety is a Python library and command-line tool designed to explore and retrieve the etymological origins of words by analyzing linguistic data and relationships between languages. It allows users to query a word and obtain its historical roots, including intermediate forms across different languages and time periods. The tool can generate recursive etymology chains as well as tree structures that visually represent how a word evolved over time. It is built as both a reusable module and a CLI...
    Downloads: 0 This Week
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  • 18
    Brain Tokyo Workshop

    Brain Tokyo Workshop

    Experiments and code from Google Brain’s Tokyo research workshop

    ...The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems.
    Downloads: 0 This Week
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  • 19
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    ...PyTorch 1.1+, and has been tested on Ubuntu 16.04/18.04/20.04, macOS 10.15, Windows 10 and Windows Subsystem for Linux. It's part of the PyTorch Ecosystem, as well as the Catalyst Ecosystem which includes Alchemy (experiments logging & visualization) and Reaction (convenient deep learning models serving).
    Downloads: 0 This Week
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  • 20
    PS-Drone

    PS-Drone

    Programming a Parrot AR.Drone 2.0 with Python - The Easy Way

    The PS-Drone-API is a full featured SDK, written in and for Python, for Parrot's AR.Drone 2.0. It was designed to be easy to learn, but it offers the full set of the possibilities of the AR.Drone 2.0, including Sensor-Data (aka NavData), Configuration and full Video-support. The video function is not restricted to mere viewing, it is also possible to analyze video images data using OpenCV2. Obviously, the PS-Drone is perfect for teaching purposes; however, even the requirements for...
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    Downloads: 12 This Week
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  • 21
    Python Tutorials

    Python Tutorials

    Machine Learning Tutorials

    ...Created by an experienced instructor and educator, the repository covers a wide range of programming basics and advanced topics. This includes foundational Python concepts, data processing with libraries like NumPy and pandas, threading and multiprocessing for concurrency, and practical use of libraries such as Matplotlib for data visualization. It also provides tutorials on machine learning frameworks and concepts, including TensorFlow, PyTorch, Keras, Scikit-Learn, and reinforcement learning techniques. ...
    Downloads: 0 This Week
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  • 22
    Gato (Graph Animation Toolbox): Animate graph algorithms for example for computing shortest paths, minimal spanning trees, maximum flows or maximal cardinality or weight matchings. Create your own animations using the Animated Data Structures (ADS).
    Downloads: 0 This Week
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  • 23
    Tensorflow 2017 Tutorials

    Tensorflow 2017 Tutorials

    Tensorflow tutorial from basic to hard

    ...This repository covers essential building blocks like sessions (for older TF versions), placeholders, variables, activation functions, and optimizers, before guiding learners through building end-to-end models for regression, classification, and data pipelines. Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. By pairing code examples with conceptual explanations, the tutorials make abstract machine learning ideas accessible and encourage experimentation with TensorBoard visualization and distributed training.
    Downloads: 0 This Week
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  • 24
    This project is intended to provide code to be used with MySQL and Python to create a database of major league baseball game events which are freely provided by the mlb.com Gameday application. Older version also support creating a retrosheet.org database but that is no longer supported. All major and minor league pitch location and game statistic data can be downloaded using BBOS. Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special...
    Downloads: 2 This Week
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  • 25
    NiftyNet

    NiftyNet

    An open-source convolutional neural networks platform for research

    An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging data. Quickly build new solutions to your own image analysis problems. ...
    Downloads: 0 This Week
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