Showing 22 open source projects for "data collection algorithm"

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  • 1
    Interpretable machine learning

    Interpretable machine learning

    Book about interpretable machine learning

    ...Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the algorithm picked up? This book will give an overview over techniques that can be used to make black boxes as transparent as possible and explain decisions. In the first chapter algorithms that produce simple, interpretable models are introduced together with instructions how to interpret the output. ...
    Downloads: 3 This Week
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  • 2
    Recommenders

    Recommenders

    Best practices on recommendation systems

    The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several...
    Downloads: 0 This Week
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  • 3
    The Grand Complete Data Science Guide

    The Grand Complete Data Science Guide

    Data Science Guide With Videos And Materials

    The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery.
    Downloads: 0 This Week
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  • 4
    Book3_Elements-of-Mathematics

    Book3_Elements-of-Mathematics

    From Addition, Subtraction, Multiplication, and Division to ML

    Book3_Elements-of-Mathematics is an open learning resource in the Visualize-ML collection that introduces core mathematical foundations required for modern data science and AI. The repository presents topics such as algebra, calculus fundamentals, and mathematical reasoning using a highly visual and beginner-friendly approach. Its goal is to reduce the intimidation barrier often associated with formal mathematics by combining diagrams, structured explanations, and applied examples. ...
    Downloads: 0 This Week
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  • 5
    Stanza

    Stanza

    Stanford NLP Python library for many human languages

    ...The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data.
    Downloads: 11 This Week
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  • 6
    List of Free Learning Resources

    List of Free Learning Resources

    Freely available programming books

    List of Free Learning Resources is a curated open-source collection of free programming resources, including books, tutorials, and courses across many languages and disciplines. Maintained by the community, it organizes materials by topic, language, and skill level, making it easy to discover learning resources. The repository includes content on software development, computer science, data science, and more.
    Downloads: 0 This Week
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  • 7
    QASystemOnMedicalKG

    QASystemOnMedicalKG

    A tutorial and implement of disease centered Medical knowledge graph

    ...It collects structured information from vertical medical websites and imports the resulting entities and relationships into Neo4j. The included graph contains diseases, symptoms, drugs, foods, examinations, departments, and commercial drug products. Python scripts handle data collection, dictionary-based segmentation, graph construction, question classification, parsing, and database queries. The chatbot recognizes many question patterns, including symptoms, causes, complications, diet guidance, medications, examinations, prevention, treatment methods, and susceptible groups. Users configure Neo4j, build the database, and launch the graph-based chat program locally. ...
    Downloads: 0 This Week
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  • 8

    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.
    Downloads: 0 This Week
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  • 9
    100 Days of Code YouTube

    100 Days of Code YouTube

    Source code for 100 days of code python course on YouTube

    100 Days of Code YouTube is a day-by-day source-code collection for a comprehensive Python programming course. The repository organizes lessons into numbered folders that progress from basic concepts to advanced language features. Early material covers variables, data types, input, strings, conditions, loops, functions, and common collections. Intermediate lessons explore exceptions, modules, file I/O, functional programming, and extensive object-oriented programming concepts. ...
    Downloads: 1 This Week
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  • 10
    The Art of Programming

    The Art of Programming

    A collection of practical tips can be found at the bottom of this page

    The Art of Programming (Second Edition) is a curated collection of programming problems and solutions originally derived from the Microsoft 100 Interview Questions blog series, later refined into a long-running tutorial and ultimately a published book. Created by July, the series began in 2010 and has since evolved into an in-depth exploration of algorithmic thinking, data structures, and coding interview preparation.
    Downloads: 1 This Week
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  • 11
    data-science-on-gcp

    data-science-on-gcp

    Source code accompanying book: Data Science on the GCP

    The data-science-on-gcp repository is a comprehensive collection of code examples and end-to-end workflows that accompany the book Data Science on the Google Cloud Platform, designed to teach developers how to build scalable data science and machine learning systems using Google Cloud services. It provides structured, chapter-aligned implementations that guide users through the full lifecycle of a data science project, including data ingestion, storage, processing, analysis, model training, and deployment. ...
    Downloads: 0 This Week
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  • 12
    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: 0 This Week
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  • 13
    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: 2 This Week
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  • 14
    interactive-coding-challenges

    interactive-coding-challenges

    120+ interactive Python coding interview challenges

    Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes.
    Downloads: 0 This Week
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  • 15
    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: 0 This Week
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  • 16
    Scikit-learn Tutorial

    Scikit-learn Tutorial

    An introductory tutorial for scikit-learn

    Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. ...
    Downloads: 0 This Week
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  • 17
    100 numpy exercises

    100 numpy exercises

    100 numpy exercises (with solutions)

    This is a collection of numpy exercises from numpy mailing list, stack overflow, and numpy documentation. I've also created some problems myself to reach the 100 limit. The goal of this collection is to offer a quick reference for both old and new users but also to provide a set of exercises for those who teach. For extended exercises, make sure to read From Python to NumPy.
    Downloads: 0 This Week
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  • 18

    fb2combiner

    This program allows embedding books in fb2 format in one, super-book.

    Fb2Combiner builds a collection of fb2-formatted books in one container (also in fb2 format). Each book is embedded as a chapter.
    Downloads: 10 This Week
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  • 19
    Matplotlib tutorial

    Matplotlib tutorial

    Matplotlib tutorial for beginner

    The Matplotlib tutorial repository is designed as a hands-on learning resource to help users — especially Python beginners — get started with Matplotlib for creating plots and charts. It provides a sequence of example scripts and notebooks that cover fundamental plotting tasks: line graphs, histograms, scatter plots, bar charts, customizing axes, labels, legends, and styling. This makes it ideal for someone learning data analysis or exploratory data visualization for the first time and...
    Downloads: 0 This Week
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  • 20
    A collection of pure Python algorithms and data structures
    Downloads: 0 This Week
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  • 21
    MBDyn_sim_suite is a collection of free pre&post-processing tools and simulation models for the open-source multi-body analysis software MBDyn forming a general purpose simulation environment for structural dynamics with an emphasis on wind turbines.
    Downloads: 0 This Week
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  • 22
    cosmos

    cosmos

    Algorithms that run our universe | Your personal library of every algo

    Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.
    Downloads: 0 This Week
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