Search Results for "google-visualization-python" - Page 26
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Showing 1023 open source projects for "google-visualization-python"
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1
PyCBC
Learn how to use PyCBC to analyze gravitational-wave data
...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. Below we give links to the tutorials that should directly work in Google Colab, however. -
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Several language bindings for the FTDI D2XX driver used in FTDI's USB products. Currently supported languages are Python (pyd2xx), Java (jd2xx), CSharp (csd2xx) and LabVIEW (lvd2xx).
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Sparse Attention
"Generating Long Sequences with Sparse Transformers" examples
Sparse Attention is OpenAI’s code release for the Sparse Transformer model, introduced in the paper Generating Long Sequences with Sparse Transformers. It explores how modifying the self-attention mechanism with sparse patterns can reduce the quadratic scaling of standard transformers, making it possible to model much longer sequences efficiently. The repository provides implementations of sparse attention layers, training code, and evaluation scripts for benchmark datasets. It highlights... -
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Ansible Examples
A few starter examples of ansible playbooks, to show features
This repository collects practical, real-world examples of using Ansible to automate infrastructure, deployments, and configurations. Each directory demonstrates a specific use case—ranging from setting up web servers, load balancers, and databases to orchestrating multi-tier applications in cloud environments. The examples highlight common Ansible practices such as organizing inventories, writing reusable playbooks, using roles, and handling variables and templates. They’re designed to be... -
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ebfformat
An Efficient Binary data Format
EBF, which stands for Efficient Binary Format, is a binary file format for reading and writing binary data easily. Reading writing routines are currently available in C,C++,Fortran,Java, Python, IDL, MATLAB. A program called ebftkpy which has a set of utility functions to work with the .ebf files , e.g., viewing the contents and getting a summary, is also provided. The EBF specification is designed to be concise and easy to understand to make it easier for others to write their own code if needed. It is also designed to simplify the programming of input output routines in different programming languages. ... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions. -
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Higher
higher is a pytorch library
higher is a specialized library designed to extend PyTorch’s capabilities by enabling higher-order differentiation and meta-learning through differentiable optimization loops. It allows developers and researchers to compute gradients through entire optimization processes, which is essential for tasks like meta-learning, hyperparameter optimization, and model adaptation. The library introduces utilities that convert standard torch.nn.Module instances into “stateless” functional forms, so... -
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Python Crawler Tutorial Starts From Zero
Python crawler tutorial, taking you from zero to one
Python Crawler Tutorial Starts From Zero is a Chinese-language learning repository that teaches web crawling from introductory concepts through practical examples. Early lessons explain HTTP requests, request analysis, the Python Requests library, and common categories of extracted data. Separate chapters cover JSON processing and regular expressions for transforming responses into structured information. -
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AdaNet
Fast and flexible AutoML with learning guarantees
AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each... -
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Brand new cheatsheets and handouts
Matplotlib 3.1 cheat sheet
The Brand new cheatsheets and handouts repo is a compact, quick-reference summary of the most commonly used plotting commands and configurations in Matplotlib, intended to serve as a handy reference for experienced users who want to recall syntax or find the right function without digging into full documentation. 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”... -
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Tensor2Tensor
Library of deep learning models and datasets
...Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. T2T was developed by researchers and engineers in the Google Brain team and a community of users. It is now deprecated, we keep it running and welcome bug-fixes, but encourage users to use the successor library Trax. -
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PerfKit Benchmarker
PerfKit Benchmarker (PKB) contains a set of benchmarks
PerfKitBenchmarker is an open-source benchmarking framework designed to measure and compare the performance of cloud infrastructure across multiple providers in a consistent and reproducible way. It allows users to evaluate metrics such as latency, throughput, provisioning time, and system performance using a standardized set of benchmarks. The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile... -
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Alfred-Workflow
Full-featured library for writing Alfred 3 & 4 workflows
Alfred-Workflow is a Python helper library for Alfred 2, 3 and 4 workflow authors, developed and hosted on GitHub. Alfred workflows typically take user input, fetch data from the Web or elsewhere, filter them and display results to the user. Alfred-Workflow takes care of a lot of the details for you, allowing you to concentrate your efforts on your workflow’s functionality. -
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GoodByeCatpcha
Solver ReCaptcha v2 Free
An async Python library to automate solving ReCAPTCHA v2 by images/audio using Mozilla's DeepSpeech, PocketSphinx, Microsoft Azure’s, Google Speech and Amazon's Transcribe Speech-to-Text API. Also image recognition to detect the object suggested in the captcha. Built with Pyppeteer for Chrome automation framework and similarities to Puppeteer, PyDub for easily converting MP3 files into WAV, aiohttp for async minimalistic web-server, and Python’s built-in AsyncIO for convenience. -
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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. -
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API Correios
API correios.com.br in Python
pycorreios is a Python library aimed at interacting with Brazil’s postal service (Correios) APIs, making it easier for developers to track shipments, calculate postage, query service availability, and integrate with Brazilian e-commerce flows. The library abstracts the raw SOAP or REST endpoints exposed by Correios, providing Pythonic methods to perform common tasks like tracking a package by its code or computing shipping cost/lead time between postal codes. -
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DeepLearning
Deep Learning (Flower Book) mathematical derivation
" Deep Learning " is the only comprehensive book in the field of deep learning. The full name is also called the Deep Learning AI Bible (Deep Learning) . It is edited by three world-renowned experts, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Includes linear algebra, probability theory, information theory, numerical optimization, and related content in machine learning. At the same time, it also introduces deep learning techniques used by practitioners in the industry, including... -
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javalang
Pure Python Java parser and tools
javalang is a pure Python library for working with Java source code. javalang provides a lexer and parser targeting Java 8. The implementation is based on the Java language spec. -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. ... -
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Pinject
A pythonic dependency injection library
Pinject is a lightweight dependency-injection library for Python that favors explicit wiring and testability over magic. Instead of global singletons, you declare providers (bindings) that describe how to construct objects, and Pinject resolves the graph by inspecting call signatures. Its container supports constructor injection and fine-grained scoping so you can share expensive resources while keeping tests isolated. -
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IfSharp
F# for Jupyter Notebooks
F# for Jupyter Notebooks. This implements F# for Jupyter notebooks. View the Feature Notebook for some of the features that are included. There's a related project of .NET Interactive which was inspired by this one but a completely rethought approach with integrated package management, VS Code support, and variable sharing between languages. If you're moving to .NET Core support it's definitely worth checking out. -
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. -
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gditools
A Python program/library aimed at GD-ROM image files.
...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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dc.js
Multi-Dimensional charting built to work natively with crossfilter
...When the filter or brush changes, all other charts are updated dynamically, using animated transitions. dc.js is an easy yet powerful javascript library for data visualization and analysis in the browser and on mobile devices. -
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Python Bible Reading Module
Python Bible Reading Module is an open source python module.
Python Bible Reading Module ( PBRM ) is an open source python module. It's designed in python 3, but should be compatible with python 2 . This module allows you to easily import different versions of the bible into your code.
