Search Results for "scikit-learn" - Page 5
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Showing 133 open source projects for "scikit-learn"
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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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benchm-ml
A benchmark of commonly used open source implementations
...It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different 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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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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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. ... -
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SWire4js
A JavaScript library for developing SWire web applications
...This is a collection of demo SWire web applications which is useful in learning how to develop with SWire and SWire4js. These apps can been tried on-line here: http://swire-web-apps-collection.sourceforge.net/ To learn more about SWire, visit https://sourceforge.net/projects/swire/ -
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deemon
Deemon Scripting Language
...Syntax is easy to read and understand and is mostly based on the common languages such as c/c++, java and python, though for those fascinated by it, reaches very deep and allows for pleasingly beautiful code to be written. If you wish to learn deemon, download any package and take a look at 'lib/tut' Note: If you've already used v100, you'll be happy to see how much deemon has grown in the five months that have passed. Keep up to date with deemon at: https://github.com/GrieferAtWork/deemon -
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char-rnn
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN)
char-rnn is a classic codebase for training multi-layer recurrent neural networks on raw text to build character-level language models that learn to predict the next character in a sequence. It supports common recurrent architectures including vanilla RNNs as well as LSTM and GRU variants, letting users compare behavior and output quality across model types. It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. ... -
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commentary.vim
Commentary.vim: comment stuff out
...It integrates naturally with . repeat and respects indentation and block selections to avoid mangling code structure. Because it piggybacks on Vim’s native model, it feels like a built-in that you learn once and use everywhere. -
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Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
...Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn in tensorflow, and much more. Codes, theory, applications, and datasets about natural language processing, robotics, computer vision, and much more. -
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libVMR
VMR - machine learning library
...libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification). -
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Start Bootstrap
A library of free and open source Bootstrap themes and templates
Start Bootstrap creates free, open source, MIT license, Bootstrap themes, templates, and code snippets for you to use on any project, guides to help you learn more about designing and developing with the Bootstrap framework, and premium Bootstrap UI products. A library of open source, free to download, MIT licensed website themes and template based on Bootstrap. All of the templates and themes featured on Start Bootstrap are up to date for Bootstrap 4! A one page agency theme. A fully developed business website. ... -
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JED
Java Editor For DataTables
...If you want to be able to not only display tabular data, but also want full CRUD (Create,Read,Update,Delete) functionality, then you need JED on the Java Platform. Supports MySQL and Oracle RDBMS on the back end. Our website has many examples on how to setup and use JED with DataTables. Be sure to visit and learn how to apply them on your next web application project. PREREQUISITE: You will need minimally the javascript files: jquery.dataTables.js dataTables.editor.js You can get these from: http://datatables.net/ and https://editor.datatables.net/ -
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Python scripts that eventually work. The goal is to put together helpful python libraries, at first to learn more about python. There will at least be a library to generate regular expressions and more should come later. The latest version of the code is available in code-git (code / svn is not maintained anymore)
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JLevel
Kogonuso JLevel - a simple java library that has changed the way html
...It is a library that is more than your ordinary Html parser applications. It has automated all tagging operations of Html inside java, this means that you are no longer required to learn how to format html String when developing application that requires html in java or even when using Servlet technology to develop your websites. Just import JLevel 2.0 and turn all the tag elements that you have ever known into simple method call. The best is there for you to discover as JLevel not only stripped off tagging in Java html , it has formulated series of shortcuts by abstracting redundant html codes that we have often repeatedly written saving you valuable time. ... -
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AutoDiscovery Library
A tiny library to add auto discovery capability into your applications
...The protocol used by the library is peer-to-peer, so you don't need a central server. The API is simple, straightforward and there are examples and full documentation to learn it in minutes. -
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flixel
flixel is a free Actionscript (Flash) library
...It provides a lightweight yet powerful base framework to build 2D games: handling rendering, input, collisions, tilemaps, particles, cameras, etc. It was designed to be easy to learn and extend, useful both for simple arcade style games and more elaborate ones. It has been used for many indie / Flash games (including commercial and contest-nominated ones), and its design emphasizes object recycling, simplicity, utilities, and using free or low-cost tools to create games.
