Search Results for "learning" - Page 80
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Showing 4819 open source projects for "learning"
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Image To Gerber Converter
Convert any image to gerber and drill files
ImageToGerber makes it easy to convert any image to gerber files, ready to send to a PCB manufacturer. More info at: https://www.imagetopcb.com Demo video: https://youtu.be/HUvt0mOHv_M Forget about spending long hours etching and drilling at home, or learning to use complicated CAD software, schematics, layout design,… And more importantly, ImageToPCB is more than just a converter, it expands the potential of your design or image. It unlocks the possibility to easily make improvements and updating your design, as you will be able to make design modifications, add a silkscreen layer, resize drill diameters, create a soldermask layer to protect copper areas and to avoid accidental shorts, convert a single-side design into a double-side or multi-layer design,… all that just by editing your image with your preferred image editor. -
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GPT-NeoX
Implementation of model parallel autoregressive transformers on GPUs
This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we... -
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XLabel
XLabel: An Explainable Data Labeling Assistant
XLabel is an open-source Streamlit app that takes an explainable machine-learning approach to visual-interactive data labeling. Predict the most probable labels using Explainable Boosting Machine (EBM). Show the contributions of each feature towards the predicted labels. Provide an option to write the labels directly into the data file (use XLabel.py) or save them in a separate file (use XLabelDL.py) Support data with multiple labels and multiple classes. -
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Merlion
A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. It supports various time series learning tasks, including forecasting, anomaly detection, and change point detection for both univariate and multivariate time series. This library aims to provide engineers and researchers a one-stop solution to rapidly develop models for their specific time series needs, and benchmark them across multiple time series datasets. -
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ACHE Focused Crawler
ACHE is a web crawler for domain-specific search
...ACHE differs from generic crawlers in sense that it uses page classifiers to distinguish between relevant and irrelevant pages in a given domain. A page classifier can be defined as a simple regular expression (e.g., that matches every page that contains a specific word) or a machine-learning-based classification model. ACHE also automatically learns how to prioritize links in order to efficiently locate relevant content while avoiding the retrieval of irrelevant pages. While ACHE was originally designed to perform focused crawls, it also supports other crawling tasks, including crawling all pages in a given web site and crawling Dark Web sites (using the TOR protocol). -
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LifeAI is an artificial intelligence system that can be applied to robotics, games, or business. It simulates key processes of our minds, such as organizing data into concepts and categories, planning actions based on their predicted outcome, and communication. LifeAI was designed to be simple, but powerful and flexible enough to have many applications.
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php-billing-app
A basic PHP/MySQL/HTML Billing APP. Meant for developers learning.
Here is PHP/MySQL/HTML code that is a sample Entry Level Billing APP. It is Free, and mostly for learning purposes. You can install on a Windows or linux server, and look at the PHP code files on your PC. -
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ElegantRL
Massively Parallel Deep Reinforcement Learning
ElegantRL is an efficient and flexible deep reinforcement learning framework designed for researchers and practitioners. It focuses on simplicity, high performance, and supporting advanced RL algorithms. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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auto-sklearn
Automated machine learning with scikit-learn
auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Auto-sklearn 2.0 includes latest research on automatically configuring the AutoML system itself and contains a multitude of improvements which speed up the fitting the AutoML system. auto-sklearn 2.0 works the same way as regular auto-sklearn. auto-sklearn is licensed the same way as scikit-learn, namely the 3-clause BSD license. -
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Unitag is a language-independent Unicode-based part-of-speech tagging system. Written entirely in ANSI-compatible C, it should (in theory) compile on any OS, but has been tested on 32-bit Windows.
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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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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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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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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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WinPayXT2023-Payroll
This is a simple payroll program, for learning Payroll and MS-Access
This is a sample/educational demo payroll program, for learning payroll and MS-Access programming. It is similar to the app WebPayXT2022, written in MS-Access. WinPayXT is for a small business, with 1-15 employees. It should give you practice in learning payroll, installing on the Windows Desktop, and learning MS-Access. The WinPayXT App calculates payroll, and produces reports for tax and accounting purposes. -
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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.