Search Results for "learning" - Page 79
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Showing 4736 open source projects for "learning"
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ML Visuals
ML Visuals contains figures and templates which you can reuse
ML Visuals is an open-source project that provides a collection of reusable diagrams, templates, and visual resources designed to improve communication in machine learning research and education. The repository contains professional-quality figures that illustrate machine learning concepts such as neural networks, optimization methods, model architectures, and common deep learning techniques. These visuals are intended to help researchers, educators, and students create clearer presentations, blog posts, and scientific papers. ... -
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Source Engine
Modified source engine (2017) developed by valve and leaked in 2020
The Source Engine repository under that particular GitHub user appears to be a custom (or forked) version of a game engine — likely an engine derived from or inspired by the classic Source engine lineage (or at least the name evokes that lineage). However, publicly-available documentation, community support or clarity about the project’s scope and maturity seems limited: the repo does not clearly advertise a full engine release or wide adoption. As such, it feels more like an experimental or... -
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ManimML
ManimML is a project focused on providing animations
ManimML is a project focused on providing animations and visualizations of common machine-learning concepts with the Manim Community Library. Please check out our paper. We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine-learning concepts. Additionally, we want to provide a set of abstractions that allow users to focus on explanations instead of software engineering. -
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Shope
This is an eCommerce minimalist template
...Because it is built with Flutter, it supports cross-platform deployment, allowing developers to target both Android and iOS from a single codebase. It also demonstrates best practices for structuring Flutter UI projects, making it a useful learning resource in addition to a production starting point. -
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BERTScore
BERT score for text generation
Automatic Evaluation Metric described in the paper BERTScore: Evaluating Text Generation with BERT (ICLR 2020). We now support about 130 models (see this spreadsheet for their correlations with human evaluation). Currently, the best model is Microsoft/debate-large-online, please consider using it instead of the default roberta-large in order to have the best correlation with human evaluation. -
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Sockeye
Sequence-to-sequence framework, focused on Neural Machine Translation
Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. You can also send questions... -
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DeepFaceLive
Real-time face swap for PC streaming or video calls
You can swap your face from a webcam or the face in the video using trained face models. There is also a Face Animator module in DeepFaceLive app. You can control a static face picture using video or your own face from the camera. The quality is not the best, and requires fine face matching and tuning parameters for every face pair, but enough for funny videos and memes or real-time streaming at 25 fps using 35 TFLOPS GPU. -
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ScikitLearn.jl
Julia implementation of the scikit-learn API
The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework. -
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MVVM
Analyze the principle of vue implementation and implement mvvm
...Because it mirrors ideas found in larger frameworks, it’s an excellent teaching aid for developers who want to understand why features like computed properties and watchers behave as they do. It is not intended as a production framework; instead, it’s a compact lab for learning the principles behind MVVM and modern reactive libraries. -
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The Art of Programming
A collection of practical tips can be found at the bottom of this page
...In July 2023, work on the second edition was announced, which expands the project with updated content, new problems inspired by recent big-tech interviews, and introductions to modern machine learning techniques such as XGBoost, CNNs, RNNs, and LSTMs. This collection serves both as a historical record of algorithm problem-solving and as a living resource for programmers preparing for interviews. -
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x-definition-beginner-xml
Uses X-definition to perform XML streaming processing
...The executable jar file's main class calls X-definition's API (slightly modified within the jar archive to short-circuit some of its complexity: see the README), and an end user can therefore focus on learning the X-definition format, which is an XML vocabulary. The project overall is an invitation to take advantage of datasets ("dumps") consisting of XML, and to hear more about X-definition! -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features)... -
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codi.vim
The interactive scratchpad for hackers
...It focuses on minimal setup so you can open a buffer, set a filetype, and start experimenting immediately. Because results update incrementally, it is useful for learning, debugging, or documenting small examples. It turns Vim into a lightweight computational notebook while keeping the modal editing experience intact. -
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Kernelhub
Kernel privilege escalation vulnerability collection
The original intention of making the project is for, learning, analyzing, and research the latest kernel vulnerabilities are not needed to see the system and related content. This project is a collection of proprietary, except for test failure or unspecified Exp, Demo GIF map. If there is an omission of the omission of CVE vulnerabilities, please join your issues and bring your use of code. -
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Infinite Monkeys Random Poetry Generator
n-grams & template generation, hyper-DADA, part of speech tagging
.... --> Inlcudes scripting language --> Dictionary editor --> ngram Generation --> Computer voice playback --> CMU pronouncing dictionary --> Part of Speech Training Interface --> Learning AI -
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Dragora GNU/Linux-Libre
An independent GNU/Linux-Libre distribution
...Dragora is founded on the concepts of simplicity and elegance, it can be run for almost any purpose (desktop, workstation, server, development, etc.). The intended audience are people interested in learning more about a GNU/Linux distribution, or simply people who are looking for quality. -
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Golang Regex Tutorial
Golang - Regular Expression Tutorial
The Golang Regex Tutorial is a comprehensive learning resource that introduces regular expressions in the Go programming language. It is organized into chapters that progress from beginner-friendly basics to more advanced applications. The tutorial includes explanations, practical examples, and a cookbook section that shows how to apply regex solutions to real-world problems. It also provides insights into alternatives and variations of regex usage within Go. -
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Front-end development blog
Front-end Development Thoughts
...It also includes articles about CSS Modules, Immutable data patterns, replacing jQuery with native JavaScript, Fetch, Flux, Relay, and Redux. The project is useful for developers who want opinionated front-end learning material in one place. It also preserves a snapshot of front-end concerns from the React and modern JavaScript transition era. -
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DiffEqOperators.jl
Linear operators for discretizations of differential equations
DiffEqOperators.jl is a package for finite difference discretization of partial differential equations. It allows building lazy operators for high order non-uniform finite differences in an arbitrary number of dimensions, including vector calculus operators. For the operators, both centered and upwind operators are provided, for domains of any dimension, arbitrarily spaced grids, and for any order of accuracy. The cases of 1, 2, and 3 dimensions with an evenly spaced grid are optimized with... -
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CodeContests
Large dataset of coding contests designed for AI and ML model training
...Each problem includes structured metadata, problem descriptions, paired input/output test cases, and multiple correct and incorrect solutions in various programming languages. The dataset is distributed in Riegeli format using Protocol Buffers, with separate training, validation, and test splits for reproducible machine learning experiments. -
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Bayesian Methods for Hackers
An introduction to Bayesian methods + probabilistic programming
Bayesian Methods for Hackers is the source repository for Bayesian Methods for Hackers, an educational book about Bayesian inference and probabilistic programming. It is written from a computation-first perspective, prioritizing intuition, examples, and executable notebooks over heavy mathematical formalism. The project introduces readers to uncertainty, Bayesian modeling, MCMC, priors, posteriors, and real-world probabilistic reasoning. It includes notebook-based chapters that let learners... -
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git-chglog
CHANGELOG generator implemented in Go (Golang)
Package chglog implements the main logic for the CHANGELOG generate. git-chglog internally uses the git command to get data to include in the CHANGELOG. The basic steps are as follows. Get all the tags. Get the commits contained between tagA and tagB. Execute all tags corresponding to the tag query that was specified in Steps 1 and 2. The compiled docker images are maintained on quay.io. git-chglog requires configuration files and templates to generate a CHANGELOG. However, it is a waste of... -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
...Its architecture automatically divides large computational tasks into smaller chunks that can be executed across multiple nodes in a cluster, allowing complex analytics, machine learning workflows, and data transformations to run efficiently at scale. Mars is particularly useful for workloads that exceed the memory capacity of a single machine or require high levels of parallel processing. -
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Compose
A machine learning tool for automated prediction engineering
Compose is a machine learning tool for automated prediction engineering. It allows you to structure prediction problems and generate labels for supervised learning. An end user defines an outcome of interest by writing a labeling function, then runs a search to automatically extract training examples from historical data. Its result is then provided to Featuretools for automated feature engineering and subsequently to EvalML for automated machine learning.