Search Results for "data visualization, research" - Page 6
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Showing 230 open source projects for "data visualization, research"
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Brand new cheatsheets and handouts
Matplotlib 3.1 cheat sheet
...It lays out common use cases (plot types, styling, figure configuration, saving/exporting, subplot layout, etc.) in a concise and organized format — often serving as a “cheat sheet” for rapid look-up. For practitioners working on data-heavy projects, dashboards, or research code where plotting is frequent, it helps speed up development by reducing context-switching and documentation navigation overhead. It is especially useful when you know roughly what you want (e.g. “I need a scatter + histogram marginal plot”) but don’t remember the exact Matplotlib call. -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
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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... -
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Extended C Library
Extended C Library
Why Is libxc needed? There doesn't exist a library for ANSI C99 for common data containers, such as vectors, trees, etc. There also also doesn't exist a library for common functionality, such as error reporting/logging, string functions, configuration management (reading config files), etc... The programmer working in C doesn't have anything analogous to the Boost C++ library. The extended C library is intended to make some headway into providing this functionality. To ensure... -
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The SBMLLayout Project provides libraries and tools for handling layout and render information of SBML Models. Supported are SBML Layout / Render Extension, CellDesigner annotations and JDesigner annotations.
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libwlocate is a shared library that can be used for location-based services. It checks for WLAN-networks that are available near to a user and retrieves the current geographic position out of them. Thus no GPS is needed for positioning. This WLAN-based geolocation happens without using any of the commercial services that do the same but track the users position and data. libwlocate instead bases on the free OpenWLANMap project.
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Happy Java Library
Multilock, Collections, Controllers, Delegates, Generators, Streams
Helps to develop and test event-based multi-threaded Java application. Because of method called as API-Evolution the Happy Java Library is fully downward compatible. The library contains following functionality: MultiLock, Parallel loops, Collections, Controllers, Generators, Delegates, Streams. -
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XcodeCoverage
Code coverage for Xcode projects (Objective-C only)
XcodeCoverage is a tool that automates the generation of code coverage reports for iOS and macOS projects. It helps developers measure how much of their code is tested, facilitating better testing practices and coverage improvement. -
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PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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MultiProgressView
An animatable view that depicts multiple progresses over time
MultiProgressView is an iOS UI component that provides an advanced progress visualization system capable of displaying multiple progress segments within a single view. Modeled after the native UIProgressView, it extends functionality by allowing developers to represent multiple concurrent progress values in a segmented format. The component is fully animatable, enabling smooth transitions when progress values change over time, which enhances the visual feedback for users. -
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nlp_chinese_corpus
Large Scale Chinese Corpus for NLP
nlp_chinese_corpus is a large-scale Chinese corpus collection for natural language processing research and development. It was created to make high-volume Chinese text data easier to access for students, researchers, and practitioners. The repository gathers several major datasets, including Chinese Wikipedia entries, news articles, encyclopedia-style question answering data, community question answering data, and Chinese-English translation sentence pairs. ... -
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Gio.js
A declarative 3D globe data visualization library built with Three.js
Gio.js is an open source library for web 3D globe data visualization built with Three.js. What makes Gio.js different is that it is simple to use Gio.js to customize a 3D data visualization model in a declarative way, add your own data, and integrate it into your own modern web application. Gio.js is an open source library for web 3D globe data visualization built with Three.js. What makes Gio.js different is that it is simple to use Gio.js to customize a 3D data visualization model in a declarative way, add your own data, and integrate it into your own modern web application. ... -
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TenorSpace.js
Neural network 3D visualization framework
...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. By applying TensorSpace API, it is more intuitive to visualize and understand any pre-trained models built by TensorFlow, Keras, TensorFlow.js, etc. -
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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. -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. ... -
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Dumper.js
A better and pretty variable inspector for your Node.js applications
Dumper.js is a small JavaScript utility for pretty-printing or serializing JavaScript objects and data structures in a human-readable, tree-like format — useful for debugging, logging, or inspecting complex nested data. When you pass an object (or array, or nested structure) through dumper.js, it outputs a representation that shows keys, nested depth, and structure clearly, making it easier to understand what’s inside compared to default JSON dumps or console.log clutter. This can be... -
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concordia
Powerful search library, best suited for computer-aided translation
Concordia - Roman goddess of agreement. Concordance searcher - tool for translators who need their translations to "agree" with one standard. Concordia is a C++ library for fast text lookup in large corpora. It uses a RAM stored index, which takes up approximately 600MB of memory for a corpus of 2 million sentences. It is based on the idea of a suffix array, enhanced by the presence of other auxiliary data structures. The effects are stunning - Concordia is able to do simple substring... -
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ANDS PID Client is a generic Java client library for accessing the ANDS Persistent Identifier service and the Digital Object Identifier Service. Written by CSIRO Australia and funded by the ANDS Australian Research Data Commons Project .
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Plotly.jl
A Julia interface to the plot.ly plotting library and cloud services
A Julia interface to the plot.ly plotting library and cloud services. Plotting functions provided by this package are identical to PlotlyJS. Please consult its documentation. In fact, the package depends on PlotlyJS.jl and reexports all the methods. -
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
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Mixup-CIFAR10
mixup: Beyond Empirical Risk Minimization
mixup-cifar10 is the official PyTorch implementation of “mixup: Beyond Empirical Risk Minimization” (Zhang et al., ICLR 2018), a foundational paper introducing mixup, a simple yet powerful data augmentation technique for training deep neural networks. The core idea of mixup is to generate synthetic training examples by taking convex combinations of pairs of input samples and their labels. By interpolating both data and labels, the model learns smoother decision boundaries and becomes more... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Incanter
Clojure-based, R-like statistical computing and graphics environment
Incanter is a Clojure-based, R-like statistical computing and visualization library running on the JVM. It integrates core numerical libraries like Parallel Colt and JFreeChart to deliver data manipulation, modeling, statistical tests, and charting in a REPL-friendly environment. Start by visiting the Incanter website for an overview, check out the documentation page for a listing of HOW-TOs and examples, and then download either an Incanter executable or a pre-built version of the latest build of Incanter, which includes all the necessary dependencies, and unpack the file (if you would like to build it from source, read Building Incanter). ... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. ...
