Search Results for "notebook" - Page 4
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Showing 121 open source projects for "notebook"
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Big Sleep
A simple command line tool for text to image generation
...This repository wraps up his work so it is easily accessible to anyone who owns a GPU. You will be able to have the GAN dream-up images using natural language with a one-line command in the terminal. User-made notebook with bug fixes and added features, like google drive integration. Images will be saved to wherever the command is invoked. If you have enough memory, you can also try using a bigger vision model released by OpenAI for improved generations. You can set the number of classes that you wish to restrict Big Sleep to use for the Big GAN with the --max-classes flag as follows (ex. 15 classes). ... -
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Pandas TA
Python 3 Pandas Extension with 130+ Indicators
Technical Analysis Indicators - Pandas TA is an easy-to-use Python 3 Pandas Extension with 130+ Indicators. Pandas Technical Analysis (Pandas TA) is an easy-to-use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns. Many commonly used indicators are included, such as: Candle Pattern(cdl_pattern), Simple Moving Average (sma) Moving Average Convergence Divergence (macd), Hull Exponential Moving Average... -
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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. -
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
SageMaker TensorFlow Serving Container is an a open source project that builds docker images for running TensorFlow Serving on Amazon SageMaker. Some of the build and tests scripts interact with resources in your AWS account. Be sure to set your default AWS credentials and region using aws configure before using these scripts. Amazon SageMaker uses Docker containers to run all training jobs and inference endpoints. The Docker images are built from the Dockerfiles in docker/. The Dockerfiles... -
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PyG2Plot
Python3 binding Plotting Library
...The library is inspired by pyecharts and is designed to make web-based charts available from Python workflows. Users create a Plot instance, set chart options, and render the result as an HTML file, HTML string, notebook preview, or JupyterLab output. It also supports JavaScript callbacks through a JS helper, which makes advanced customization possible when chart behavior needs JavaScript logic. Overall, it is a useful visualization bridge for Python users who want AntV-style charts in scripts, notebooks, or web outputs. -
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Leanote Desktop App
Leanote Desktop App, based on Electron(atom-shell)
Leanote Desktop App, based on Electron(atom-shell). Use Leanote as a notebook/note, and manage your knowledge on Leanote. Do you like markdown? don't worry, Leanote support it. You can public your knowledge then Leanote is your blog! An awesome blog where you can create your own theme. Share your knowledge with your friends on Leanote. Collaborate with friends to improve your knowledge. -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and... -
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Lucid
A collection of infrastructure and tools for research
...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 entirely in the cloud. You can run the notebooks on your local machine, too. Clone the repository and find them in the notebooks subfolder. You will need to run a local instance of the Jupyter notebook environment to execute them. Feature visualization answers questions about what a network, or parts of a network, are looking for by generating examples. -
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nbdev template
Template for nbdev projects
Write, test, document, and distribute software packages and technical articles, all in one place, your notebook. Traditional programming environments throw away the result of your exploration in REPLs or notebooks. nbdev makes exploration an integral part of your workflow, all while promoting software engineering best practices. -
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AnyBar
OS X menubar status indicator
AnyBar is a small indicator for your menubar that does one simple thing: it displays a colored dot. What the dot means and when to change it is up to you. AnyBar is controlled via a UDP port (1738 by default). Before any commands can be sent, AnyBar.app must be launched. Once launched, you may send it a message to change the style of the dot. black and white always has black or white fill. On Big Sur, where text color of menubar might change depending on the wallpaper, you might want to use... -
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Kalman and Bayesian Filters in Python
Kalman Filter book using Jupyter Notebook
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions. Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. -
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fastpages
Blogging platform, with enhanced support for Jupyter Notebooks
...A full list of features can be found on GitHub. Create posts containing code, outputs of code (which can be interactive), formatted text, etc directly from Jupyter Notebooks; Notebook posts support features. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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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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nodebook
Multi-Lang Web REPL
...Click "Run" or press Ctrl+Enter or Cmd+Enter to run your code. Code is automatically persisted on the file system. You can also use Nodebook directly on the command line, running your notebooks upon change. A notebook is a folder containing an {index|main}.{js,py,c,cpp,...} file. The homepage lists all of the available notebooks. Click on the + Notebook button on the Home page, then select the language of the notebook to be created. Once on the notebook edition page, you can rename the notebook by clicking on it's name. Notebooks are created in the directory specified by the parameter --notebooks. -
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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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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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TheoremJS
A Math library for computation in JavaScript
...It was designed to fit your need, whatever you are trying to do. With TheoremJS, you won't feel the need of running the code on a server, you can run it right on the browser, or on a NodeJS notebook (Jupyter like). Even though we loose performances with BigNumber, our algorithms are well-engineered and ensure decent performances on every device. You can use TheoremJS for every project, ranging from doing your math homework to launching a rocket into deep space. (Ok, maybe if you're planning to launch a rocket into space, you might want to use other tools in addition to TheoremJS). -
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Climate Modeling Courseware
Interactive lecture notes and assignments in Jupyter notebook format
...The focus of the course is on the hands-on use of both simple and complex climate models to build an understanding of the processes that control the planetary energy budget. The course makes extensive use of Python code and the Jupyter notebook for reproducible, self-describing calculations and figures. This repository contains a collection of linked Jupyter notebooks with lecture notes, examples and assignments. All notebooks are self-describing. -
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Jupyter Themes
Custom Jupyter Notebook Themes
...Because it modifies the Notebook’s CSS, the project focuses on lightweight overrides rather than invasive changes, minimizing breakage across notebook versions. It’s especially valued by power users who spend long hours in notebooks and want a consistent, eye-friendly environment. -
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BeakerX
Beaker Extensions for Jupyter Notebook
...Widgets for time-series plotting, tables, forms, and more (there are Python and JavaScript APIs in addition to the JVM languages). Polyglot magics and autotranslation, allowing you to access multiple languages in the same notebook, and seamlessly communicate between them. Apache Spark integration including GUI configuration, status, progress, interrupt, and tables. One-click publication with interactive plots and tables, and Jupyter Lab. BeakerX is available via conda, pip, and docker. Or try it live online with Binder. All of BeakerX’s JVM languages plus Python and JavaScript have APIs for interactive time-series, scatter plots, histograms, heatmaps, and treemaps. -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. -
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vimpyter
Edit your Jupyter notebooks in Vim/Neovim
Input/output cells are displayed using a custom syntax file and folding. See your edits by starting Jupyter Notebook/Nteract application with a single command/mapping (just remember to save your modifications). You may have to reload the browser page/app to see the effects. -
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pivottablejs
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook
PivotTable.js is a Javascript Pivot Table and Pivot Chart library with drag-drop interactivity, and it can now be used with Jupyter/IPython Notebook via the pivottablejs module. I first built PivotTable.js with a plan to build an in-browser data analysis tool, and got as far as one where you could load up a CSV file in the browser for display. Since then, however, the Jupyter project has gathered steam and now provides a browser-based interface to some of the most powerful data processing libraries in the world, so it makes sense to interface with it.
