Search Results for "scikit-learn" - Page 28
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Showing 1969 open source projects for "scikit-learn"
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
...Magnetic sensing separates the electronic circuitry from the passive-interface, making it easier to replace interfaces as they wear out while allowing for a wide variety of form factors. Machine learning allows us to learn sensor response models that are robust to variations across fabrication and time, and our self-supervised learning algorithm enables finer performance enhancement. -
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scikit-learn tips
50 scikit-learn tips
scikit-learn-tips is an educational repository that collects practical advice and best practices for using the scikit-learn machine learning library effectively. The project consists of short explanations and examples that highlight common patterns, pitfalls, and techniques used when building machine learning workflows in Python. Each tip typically demonstrates how specific components of scikit-learn, such as pipelines, preprocessing utilities, or model evaluation tools, should be applied in real projects. ... -
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Materialized CMS
A Content Management System for IIS using Materialize CSS Framework.
Materialized CMS is a Content Management System using Materialize CSS. We design and designed it for ourself because we like to develop and learn new stuff. We also decided to share our work to the World, maybe someone have use of it. For now it is in an Early Access Phase and you should have some experince hosting websites if you want to use this Software. However, it is free to use for everyone and it will get updates from time to time. -
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3D Learn to Read Music Game in Python
3D Learn to Read Music Game in Python
The game runs on win 7 after its run in win XP compatiability mode (so right click on game to select the SP3). This game to help beginners learn to read sheet music in a fun and easy way. More specifically this game is to learn sheet music restricted to the treble staff and (optionally) their ear training for the treble staff. This Panda3D game project is composed of 7 sub-programs in the project-one program is to deal with the menu, another is the main game code, another program deals with the extra graphics, another is the code for the readme dialog box. ... -
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Walrus
Lightweight Python utilities for working with Redis
The purpose of walrus is to make working with Redis in Python a little easier. Rather than ask you to learn a new library, walrus subclasses and extends the popular redis-py client, allowing it to be used as a drop-in replacement. In addition to all the features in redis-py, walrus adds support for some newer commands, including full support for streams and consumer groups. Persistent structures implemented on top of Hashes. Supports secondary indexes to allow filtering on equality, inequality, ranges, less/greater-than, and a basic full-text search index. ... -
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X11-Basic
A BASIC interpreter and compiler with graphics.
X11-Basic is a dialect of the BASIC programming language with graphics capability that integrates features like shell scripting, cgi-Programming and full graphical visualisation into the easy to learn basic language on modern computers. -
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Javis
Julia Animations and Visualizations
Javis: Julia Animations and Visualizations. Javis makes generating simple animations a breeze! Want to learn more? Check out our documentation for tutorials, our contributing guidelines, and the mission of Javis.jl. We have a live Zulip stream that you can join to discuss Javis with other Javis users. -
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MuZero General
A commented and documented implementation of MuZero
muzero-general is an open-source implementation of the MuZero reinforcement learning algorithm introduced by DeepMind. MuZero is a model-based reinforcement learning method that combines neural networks with Monte Carlo Tree Search to learn decision-making policies without requiring explicit knowledge of the environment’s dynamics. The repository provides a well-documented and commented implementation designed primarily for educational purposes. It allows researchers and developers to train reinforcement learning agents that can learn to play games such as Atari environments or board games. ... -
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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. -
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AppWorks
Front-end R&D tool set based on VS Code plug-in
Use AppWorks to develop Universal Applications quickly. Click "Shop Icon" on the Activity Bar of VS Code. Enter "app works" in the input box to search. Click the Install button on the first app works option. After installation is successful, click the "AppWorks icon" on the Activity Bar of VS Code to start. We have integrated the operations of creating, debugging, and publishing projects into commonly used editors through plug-ins, making the project development process easier. We provide a... -
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MyABCs
Learn the English alphabet
An educational game for young children. MyABCs familiarizes children with the English alphabet and a keyboard. -
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ModelFox
ModelFox makes it easy to train, deploy, and monitor ML models
ModelFox makes it easy to train, deploy, and monitor machine learning models. Train a model from a CSV file on the command line. Make predictions from Elixir, Go, JavaScript, PHP, Python, Ruby, or Rust. Learn about your models and monitor them in production from your browser. ModelFox makes it easy to train, deploy, and monitor machine learning models. You can install the modelfox CLI by either downloading the binary from the latest GitHub release or by building from source. Train a machine learning model by running modelfox train with the path to a CSV file and the name of the column you want to predict. ... -
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Learn and Play
XML-based framework for developing games
XML-based framework for developing games in (ActionScript 2.0, discontinued) HTML5 Phaser.io's engine It'd been thought to develope a project with a great amount of games on drag&drop, painting, typing, hunting, puzzles.There's no need to write the same code to similar games! Just write some XML lines (check samples) and one JavaScript instruction to run your game. NOTE: some browsers security policies do not allow to run samples locally. If this occurs, try to publish on a web site -
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lightning library
Large-scale linear classification, regression and ranking in Python
lightning is a library for large-scale linear classification, regression and ranking in Python. -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
...It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the full image—making pretraining computationally efficient. After pretraining, the encoder serves as a powerful backbone for downstream tasks like image classification, segmentation, and detection, achieving top performance with minimal fine-tuning. ... -
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Scikit-Optimize
Sequential model-based optimization with a `scipy.optimize` interface
Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn. -
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The fastai book
The fastai book, published as Jupyter Notebooks
...The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo for your own private use. No commercial or broadcast use is allowed. We are making these materials freely available to help you learn deep learning, so please respect our copyright and these restrictions. -
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Awesome Conformal Prediction
A professionally curated list of awesome Conformal Prediction videos
awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing in Conformal Prediction under the supervision of its creator, Prof. Vladimir Vovk. Since 2015, I have painstakingly gathered these invaluable resources, and upon completing my PhD (my thesis, "Machine Learning for Probabilistic Prediction," can be found in the "Theses" section), I am thrilled to share my expertise with the global machine learning community. ... -
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Aurelia
Framework entry point bringing together all the sub-modules of Aurelia
...Aurelia's standards-based, unobtrusive style makes it the only framework that empowers you to build components using vanilla JavaScript or TypeScript. If you know modern JS and HTML, there's little more to learn to build even the most complex apps. -
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Create React App
Set up a modern web app by running one command
Create React App lets you create React apps quickly and easily-- no learning of build tools or build configurations necessary. All you need is one command, and you can get started in seconds. All tools are preconfigured and hidden, and with instant reloads you can focus on code, not build tools. With Create React App your apps need only one build dependency, so everything works together seamlessly, and when it’s time to deploy your bundles are automatically optimized. With Create... -
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LayoutParser
A Unified Toolkit for Deep Learning Based Document Image Analysis
...This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser. After several major updates, layoutparser provides various functionalities and deep learning models from different backends. But it still easy to install layoutparser, and we designed the installation method in a way such that you can choose to install only the needed dependencies for your project. ... -
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PyTorch Handbook
The pytorch handbook is an open source book
PyTorch Handbook is an open-source educational project designed to help developers and researchers quickly learn deep learning using the PyTorch framework. The repository functions as an online handbook that explains how to build, train, and evaluate neural network models using PyTorch. It includes tutorials and examples that demonstrate common deep learning tasks such as image classification, neural network design, model training workflows, and evaluation techniques. -
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CodeIgniter
Open Source PHP Framework (originally from EllisLab)
CodeIgniter is a lightweight PHP web framework that focuses on simplicity, performance, and minimal configuration to get started quickly. It adopts an MVC-style or loosely structured approach depending on developer preference, with core components for routing, input handling, output views, and database abstraction. The framework provides convenience libraries for sessions, form validation, encryption, email, file uploads, and more, all optional so the footprint stays small. Because it... -
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Microsoft OpenPAI FrameworkController
General-Purpose Kubernetes Pod Controller
...In the open source community, there are so many specialized Kubernetes Pod controllers which are built for a specific kind of application, such as Kubernetes StatefulSet Controller, Kubernetes Job Controller, KubeFlow TensorFlow Operator, KubeFlow PyTorch Operator. However, no one is built for all kinds of applications and combination of the existing ones still cannot support some kinds of applications. So, we have to learn, use, develop, deploy and maintain so many Pod controllers. Partitioned to different heterogeneous TaskRoles which share the same lifecycle. Ordered in the same homogeneous TaskRole by TaskIndex. With consistent identity {FrameworkName}-{TaskRoleName}-{TaskIndex} as PodName. -
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YOLOv3
Object detection architectures and models pretrained on the COCO data
Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an expert. Students love YOLOv5 for its simplicity and there are many quickstart examples for you to get started within seconds. ...
