Showing 4819 open source projects for "learning"

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  • 1
    TechCPP

    TechCPP

    C++ learning and interview guide aimed at back-end systems developers

    TechCPP is a comprehensive C++ learning and interview guide aimed at back-end and systems developers preparing for professional roles. It gathers frequently asked concepts and deep dives—value categories (lvalue/rvalue), perfect forwarding, casts, memory models, atomics, and more—into a structured, readable format. The material goes beyond syntax to discuss performance, optimization techniques, and how standard library containers are implemented under the hood.
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  • 2
    Hello JavaScript

    Hello JavaScript

    Course repository designed to teach JavaScript from scratch in Spanish

    ...Exercises and lesson organization make it easy to follow along, practice, and review concepts as you go. The repository is openly licensed and structured so you can clone it, experiment locally, and track your learning progress. It’s a solid on-ramp for beginners who want a guided, project-based journey into JavaScript fundamentals and practical usage.
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  • 3
    The Hypersim Dataset

    The Hypersim Dataset

    Photorealistic Synthetic Dataset for Holistic Indoor Scene

    Hypersim is a large-scale, photorealistic synthetic dataset and tooling suite for indoor scene understanding research. It provides richly annotated renderings—RGB, depth, surface normals, instance and semantic segmentations, and material/lighting metadata—produced from high-fidelity virtual environments. The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and...
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  • 4
    Image Fusion

    Image Fusion

    Deep Learning-based Image Fusion: A Survey

    This repository is a survey / code collection centered on deep learning–based image fusion (e.g. fusing infrared + visible light images, multi-modal fusion) methods. It catalogs many fusion algorithms (e.g. DenseFuse, FusionGAN, NestFuse, etc.), links to code implementations, and describes evaluation metrics. The repository includes a “General Evaluation Metric” subfolder containing objective fusion metrics.
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  • 5
    Optax

    Optax

    Optax is a gradient processing and optimization library for JAX

    Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize...
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  • 6
    Hamilton DAGWorks

    Hamilton DAGWorks

    Helps scientists define testable, modular, self-documenting dataflow

    Hamilton is a lightweight Python library for directed acyclic graphs (DAGs) of data transformations. Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters. As...
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  • 7
    Fairlearn

    Fairlearn

    A Python package to assess and improve fairness of ML models

    Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms...
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  • 8
    NeuroMatch Academy (NMA)

    NeuroMatch Academy (NMA)

    NMA Computational Neuroscience course

    NMA Computational Neuroscience course. We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. The Neuro Video Series is a series of 12 videos that covers basic neuroscience concepts and neuroscience methods. These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you...
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  • 9
    Sacred

    Sacred

    Sacred is a tool to help you configure, andorganize IDSIA experiments

    Sacred is a tool to help you configure, organize, log and reproduce experiments. It is designed to do all the tedious overhead work that you need to do around your actual experiment. A very convenient way of the local variables in a function to define the parameters your experiment uses. You can access all parameters of your configuration from every function. They are automatically injected by name. You get a powerful command-line interface for each experiment that you can use to change...
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  • 10
    Aim

    Aim

    An easy-to-use & supercharged open-source experiment tracker

    Aim logs all your AI metadata (experiments, prompts, etc) enabling a UI to compare & observe them and SDK to query them programmatically. The Aim standard package comes with all integrations. If you'd like to modify the integration and make it custom, create a new integration package and share with others. Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. The two most famous AI metadata applications are: experiment...
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  • 11
    flair

    flair

    A very simple framework for state-of-the-art NLP

    A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), sentiment analysis, part-of-speech tagging (PoS), special support for biomedical texts, sense disambiguation and classification, with support for a rapidly growing number of languages. A text embedding library. Flair has...
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  • 12
    stdlib

    stdlib

    Standard library for JavaScript and Node.js

    A standard library for javascript and node.js. High performance, rigorous, and robust mathematical and statistical functions. Build advanced statistical models and machine learning libraries. Plotting and graphics functionality for data visualization and exploratory data analysis. Analyze and understand your data. Comprehensively tested utilities for application and library development. Functions to assert, group, filter, map, pluck, and transform your data both in browsers and on the server. Everything you would expect from a modern standard library. ...
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  • 13
    KubeBlocks

    KubeBlocks

    KubeBlocks is an open-source control plane that runs and manages datab

    Building data infrastructure on K8s has become increasingly popular. However, the most prominent obstacles are the difficulties of integrating with cloud providers, the lack of reliable operators, and the steep learning curve of K8s. KubeBlocks offers an open-source option that helps application developers and platform engineers set up feature-rich services for RDBMS, NoSQL, streaming and analytical systems. No need to be a K8s professional, anyone can set up a full-stack, production-ready data infrastructure in minutes. KubeBlocks extends K8s StatefulSet capability with ReplicationSet and ConsensusSet workloads. ...
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  • 14
    JDF.jl

    JDF.jl

    Julia DataFrames serialization format

    JDF is a DataFrames serialization format with the following goals, fast save and load times, compressed storage on disk, enabled disk-based data manipulation (not yet achieved), and support for machine learning workloads, e.g. mini-batch, sampling (not yet achieved). JDF stores a DataFrame in a folder with each column stored as a separate file. There is also a metadata.jls file that stores metadata about the original DataFrame. Collectively, the column files, the metadata file, and the folder is called a JDF "file". JDF.jl is a pure-Julia solution and there are a lot of ways to do nifty things like compression and encapsulating the underlying struture of the arrays that's hard to do in R and Python. ...
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  • 15
    Hello Algorithm

    Hello Algorithm

    Animated illustrations, one-click data structure

    ...This project aims to create an open source, free, novice-friendly introductory tutorial on data structures and algorithms. The whole book uses animated illustrations, the content is clear and easy to understand, and the learning curve is smooth, guiding beginners to explore the knowledge map of data structures and algorithms. The source code can be run with one click, helping readers improve their programming skills during exercises and understand the working principles of algorithms and the underlying implementation of data structures. Readers are encouraged to help each other learn, and questions and comments can usually be answered within two days.
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  • 16
    PyTensor

    PyTensor

    Python library for defining and optimizing mathematical expressions

    PyTensor is a fork of Aesara, a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that...
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  • 17
    Flyte
    Build production-grade data and ML workflows, hassle-free The infinitely scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks. Don’t let friction between development and production slow down the deployment of new data/ML workflows and cause an increase in production bugs. Flyte enables rapid experimentation with production-grade software. Debug in the cloud by iterating on the workflows locally to achieve tighter feedback loops. As your...
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  • 18
    Dasar Pemrograman Golang

    Dasar Pemrograman Golang

    Source Code E-book Dasar Pemrograman Golang

    ...We will focus on learning basic science needed for developing web applications using Go, including such as: routing, multiplexers, middleware, cookies, and others.
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  • 19
    x-transformers

    x-transformers

    A simple but complete full-attention transformer

    A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through...
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  • 20
    Java Design Patterns

    Java Design Patterns

    Design patterns implemented in Java

    A comprehensive, community-maintained collection of design pattern implementations in Java, offering well-documented, educational examples to help developers understand and apply common architectural solutions. All designs should be as simple as possible. You should start with KISS, YAGNI, and Do The Simplest Thing That Could Possibly Work principles. Complexity and patterns should only be introduced when they are needed for practical extensibility. The design patterns are now available as...
    Downloads: 8 This Week
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  • 21
    MediaCrawler

    MediaCrawler

    Self-media platform crawler

    ...Users can search by keyword, crawl specific posts, collect nested comments, and retrieve creator profiles. It also supports cached login states, proxy pools, and comment word-cloud generation. The repository is intended for learning and research, with clear restrictions against illegal, large-scale, or commercial scraping.
    Downloads: 5 This Week
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  • 22
    Kornia

    Kornia

    Open Source Differentiable Computer Vision Library

    Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within...
    Downloads: 2 This Week
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  • 23
    free-for.dev

    free-for.dev

    A list of SaaS, PaaS and IaaS offerings that have free tiers

    free-for-dev is a long-running, community-curated catalog of services that offer free tiers useful to developers, students, makers, and small teams. The list spans hosting, databases, CI/CD, monitoring, source control, APIs, design tools, and more, organized into clear categories so readers can scan and compare options quickly. It emphasizes practical limits such as usage caps, seat counts, rate limits, and time-boxed trials, helping users spot real-world constraints before adopting a tool....
    Downloads: 19 This Week
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  • 24
    doccano

    doccano

    Open source annotation tool for machine learning practitioners

    doccano is an open-source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence-to-sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours.
    Downloads: 2 This Week
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  • 25
    Orange Data Mining

    Orange Data Mining

    Orange: Interactive data analysis

    Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections.
    Downloads: 24 This Week
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