Search Results for "learn" - Page 4
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Showing 118 open source projects for "learn"
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CameraVoyeur
Windows-oriented utility to log frames from a connected camera devices
CameraVoyeur is a small Windows-oriented utility that demonstrates how to capture, preview, and possibly log frames from a connected camera device in a lightweight way. It’s set up more like an experiment or proof-of-concept than a polished end-user app, focusing on the plumbing for grabbing images from the webcam. The project shows how to access the camera stream, keep it running, and expose the captured output for later use or display. Because it’s in a regular GitHub repo and not a closed... -
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Differentiable Neural Computer
A TensorFlow implementation of the Differentiable Neural Computer
The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the model to learn how to store and retrieve information across long time horizons, much like a traditional computer. ... -
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Omnipay
A framework agnostic, multi-gateway payment processing library
...It has been designed based on ideas from Active Merchant, plus experience implementing dozens of gateways for CI Merchant. It has a clear and consistent API, is fully unit tested, and even comes with an example application to get you started. You can learn one API and use it in multiple projects using different payment gateways. If you need to change payment gateways you won’t need to rewrite your code. Most official PHP payment gateway libraries are a mess. Most payment gateways have exceptionally poor documentation. So, why use Omnipay instead of a gateway’s official PHP package/example code? ... -
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Flutter Notebook
Collection of demo projects for Flutter
Flutter-Notebook is a curated collection of small demo projects for Flutter, designed to help developers learn and practice Flutter UI patterns and behaviors by example. The repository gathers many independent “mini apps” (each focused on one or a few features) so that learners can inspect, run, and understand individual Flutter behaviors in isolation. Demo of common UI behaviors (pull-to-refresh, left-swipe delete, JSON deserialization). -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs... -
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Easy Rules
The simple, stupid rules engine for Java
...This means only bug fixes will be addressed from now on. Version 4.1.x is the only supported version. Please consider upgrading to this version at your earliest convenience. Lightweight library and easy-to-learn API. POJO-based development with an annotation programming model. Useful abstractions to define business rules and apply them easily with Java. The ability to create composite rules from primitive ones. The ability to define rules using an Expression Language (Like MVEL, SpEL and JEXL) -
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JavaScript Array Explorer
A resource to figure out what JavaScript array method would be best
...The tool provides visual examples, explanations of method semantics, and code snippets you can copy into your own project. Because many JavaScript learners struggle with which array method to choose or misuse them, this resource offers an approachable way to learn by doing and exploring rather than memorizing. The front-end is friendly and responsive, with filtering UI that lets you narrow based on the kind of task you’re performing. -
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NG6
An AngularJS Starter repo for AngularJS + ES6 + Webpack
...Styles are handled via SASS (node-sass), with each component encouraged to bundle its own styles, templates, and tests for strong locality. Overall, NG6-starter is designed as a “de facto” reference for developers who want to learn and adopt a modern workflow. -
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Flutter Dojo
A beautiful design and useful project
Flutter Dojo is an educational and practical Flutter UI project that provides a large collection of demo screens, layouts, and component examples designed to help developers learn and experiment with Flutter’s capabilities. Rather than being a traditional component library, it acts as a showcase and playground where developers can explore different UI patterns, animations, and design implementations within a single project. The repository includes numerous real-world interface examples, allowing developers to study how complex layouts and interactions are structured in Flutter applications. ... -
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Dart
Dart is a client-optimized language for fast apps on any platform
...A programming language optimized for building user interfaces with features such as sound null safety, the spread operator for expanding collections, and collection if for customizing UI for each platform. A programming language that is easy to learn, with a familiar syntax. Make changes to your source code iteratively, using hot reload to instantly see the effect in the running app. -
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PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
...We use PyCBC in the detection of gravitational waves from binary mergers such as GW150914. These examples explore how to analyze gravitational wave data, how we find potential signals and learn about them. Many of these tutorials will require you to make edits to config files as part of their exercises. At the moment this isn't easy to do on services like Google Colab. However, you can do them either on your local machine or by using services such as mybinder or sciserver which allow a full juypterhub experience with the ability to view and edit text files. ... -
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Flutter Example Apps
Basic Flutter apps, for flutter devs
FlutterExampleApps is a curated repository of Flutter application source code and demos intended to help developers learn Flutter development through real-world examples and practical implementations of common app patterns. Instead of being a single app, it consists of dozens of example projects including clones of popular apps, utility apps, interactive UIs, and Flutter integrations with plugins and device features, covering topics from basic widgets to Firebase integration and responsive layouts. ... -
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Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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The Neural Process Family
This repository contains notebook implementations
Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. They can learn distributions over functions from data and efficiently make predictions at new inputs with calibrated uncertainty — making them useful for few-shot learning, Bayesian regression, and meta-learning. Each notebook includes theoretical explanations, key building blocks, and executable code that runs directly in Google Colab, requiring no local setup. ... -
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gditools
A Python program/library aimed at GD-ROM image files.
...It can be used to list files, extract data, generate sorttxt file, extract bootstrap (IP.BIN) file and more. This project can be used in standalone mode, in interactive mode or as a library in another Python program (check the 'addons' folder to learn how). For your convenience, you can use the gditools.py GUI program supplied in the Files section (optional). To use this project you must install the Python 2.7.x branch release binaries. See the README.TXT file for more informations. -
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HTML5 Demos and Examples
Collection of hacks and demos showing capability of HTML5 apps
...The repository is an archive of interactive examples—ranging from canvas tricks to video, audio, drag-and-drop, WebSockets, and more—that illustrate how HTML, CSS, and JavaScript can combine to build rich, browser-centric experiences without plugins. Each demo is a self-contained piece of code you can open, explore, and learn from, and the collection was curated to help developers grasp emerging standards at a time when HTML5 was gaining traction and not yet ubiquitous. Though no longer actively maintained, the archive still contains hundreds of creative examples that can teach fundamentals and spur experimentation with web features. Developers historically used it as a reference when testing browser support for features or teaching newcomers how specific APIs behave in real code. -
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benchm-ml
A benchmark of commonly used open source implementations
...The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories. -
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Javaluator
A java infix evaluator based on "Shunting Yard" algorithm.
... - Localizable: Define localized names for functions or constants. - Syntax check - Small footprint: 26kB, no additionnal library required. - Fully documented Please visit the project site to learn more : http://javaluator.fathzer.com If you use Javaluator in your product, we will be happy to add a link to your product in the Javaluator web site. Send an email to javaluator@fathzer.com. If you think Javaluator is valuable, vote up below. -
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TenorSpace.js
Neural network 3D visualization framework
...TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization of pre-trained models from TensorFlow, Keras and TensorFlow.js. TensorSpace is a neural network 3D visualization framework designed for not only showing the basic model structure but also presenting the processes of internal feature abstractions, intermediate data manipulations and final inference generations. ... -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. ... -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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Oboe.js
A streaming approach to JSON
Oboe.js is a streaming approach to JSON. Oboe.js speeds up web applications by providing parsed objects before the response completes. Oboe.js is an open source Javascript library for loading JSON using streaming, combining the convenience of DOM with the speed and fluidity of SAX. It can parse any JSON as a stream, is small enough to be a micro-library, doesn't have dependencies, and doesn't care which other libraries you need it to speak to. We can load trees larger than the available... -
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Keras resources
Directory of tutorials and open-source code repositories
Keras resources is a curated directory of tutorials, projects, and educational materials designed to help developers learn and work effectively with the Keras deep learning library. It aggregates a wide range of resources, including beginner guides, advanced tutorials, code examples, and third-party tools, all organized into a single reference hub. The repository covers diverse topics such as image classification, natural language processing, reinforcement learning, and generative models, providing both theoretical and practical insights. ... -
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Synaptic
Architecture-free neural network library for node.js and the browser
Synaptic is a javascript neural network library for node.js and the browser, its generalized algorithm is architecture-free, so you can build and train basically any type of first order or even second order neural network architectures. This library includes a few built-in architectures like multilayer perceptrons, multilayer long-short term memory networks (LSTM), liquid state machines or Hopfield networks, and a trainer capable of training any given network, which includes built-in... -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. ...
