Search Results for "notebook" - Page 9
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Showing 386 open source projects for "notebook"
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rayshade-mathematica
rayshade and POV for Mathematica Export + view
Beautifully Render* your Graphic3D and Shown or Manipulate right in the Front End (without Export to, ie 3DStudio Art Renderer, et al). For use with Mathematica 4.0 - 13.1. Makes file.ray or .pov that will look much like image in notebook except rendered. Works easily/automatically with many Graphics3D (and some Graphic) as well. However graphics in 13.1 is too big to comment on: many will work many not. Has many options to fix renders that aren't so auto. Now very portable (Apple, Microsoft, Linux) supported (given rayshade or povray binary download or compiled). ... -
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Disco Diffusion
Notebooks, models and techniques for the generation of AI Art
A frankensteinian amalgamation of notebooks, models, and techniques for the generation of AI art and animations. This project uses a special conversion tool to convert the Python files into notebooks for easier development. What this means is you do not have to touch the notebook directly to make changes to it. The tool being used is called Colab-Convert. Initial QoL improvements added, including user-friendly UI, settings+prompt saving, and improved google drive folder organization. Now includes sizing options, intermediate saves and fixed image prompts and Perlin inits. the unexposed batch option since it doesn't work. -
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PyTTI-Notebook
PyTTI-Notebook
Recent advances in machine learning have created opportunities for “AI” technologies to assist unlocking creativity in powerful ways. PyTTI is a toolkit that facilitates image generation, animation, and manipulation using processes that could be thought of as a human artist collaborating with AI assistants. The underlying technology is complex, but you don’t need to be a deep learning expert or even know coding of any kind to use these tools. Understanding the underlying technology can be... -
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EZStacking
EZStacking is Jupyter notebook generator for machine learning
EZStacking is Jupyter notebook generator for supervised learning problems using Scikit-Learn pipelines and stacked generalization. EZStacking handles classification and regression problems for structured data. It can also be viewed as a development tool, because a notebook generated with EZStacking contains: -an exploratory data analysis (EDA) used to assess data quality - a modelling producing a reduced-size stacked estimator - a server returning a prediction, a measure of the quality of input data and the execution time. -
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RetroLab
JupyterLab distribution with a retro look and feel
RetroLab (also known as JupyterLab Retro, previously called JupyterLab Classic) is a JupyterLab distribution with a retro look and feel, more similar to the classic Jupyter notebook. -
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pyGiNaC
pyGiNaC (maintained)
This is a refresh and maintained version of the previous stalled project https://sourceforge.net/projects/pyginac/ It works with the current version of GiNaC. See an introduction here: http://moebinv.sourceforge.net/pyGiNaC.html -
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ipynb-quicklook
Generator for Jupyter/IPython notebooks without further dependencies
A Quick Look generator for Jupyter/IPython notebooks without further dependencies. This plugin has now been integrated into a native macOS app, Jupyter Notebook Viewer. This is the recommended way to install the QuickLook generator. A stand-alone Quick Look generator for Jupyter/IPython notebooks on macOS. Contents are rendered on-the-fly using nbviewer.js. -
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NSFW Data Scraper
Collection of scripts to aggregate image data
NSFW Data Scraper is an open-source project that provides scripts for automatically collecting large datasets of images intended for training NSFW image classification systems. The repository focuses on aggregating image data from various online sources so that developers can build datasets suitable for training content moderation models. These datasets typically contain images categorized into different classes associated with adult or explicit content, which can then be used to train... -
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Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
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pyDesk OS
An Xubuntu-based distro with Python dev tools
PyDesk is an Xubuntu-based distribution with basic development tools of Python. In the current version, IDLE, pip, venv and Jupyter Notebook are pre-installed. -
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elastic-jupyter-operator
Cloud-native way to provide elastic Jupyter Notebooks on Kubernetes
Jupyter is a free, open-source, interactive web tool known as a computational notebook, which researchers can use to combine software code, computational output, explanatory text, and multimedia resources in a single document. For data scientists and machine learning engineers, Jupyter has emerged as a de facto standard. At the same time, there has been growing criticism that the way notebooks are being used leads to low resource utilization. -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
...These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance. -
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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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ipycytoscape
A Cytoscape Jupyter widget
A widget enabling interactive graph visualization with cytoscape.js in JupyterLab and the Jupyter Notebook. -
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Java-based language learning utility for vocabulary augmentation. - Insert words ( suggestions from Google ) - Make tests - Search and filter - Export/Import ( PDF, XML, XLS) - Conjugate - View corresponding images.
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OBDGeek
configurable OBDII diagnostics software
...Recorded communication can be used for simulation - this way users can tune they configuration files at home without the necessity of connected car. The software is designed to be run on a PC (notebook). It is written in Java. Thanks to that, it can run on Windows, Linux and Mac OS machines. -
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Train Invaders
Jupyter Notebook + Space Invaders
Training a model can be a long long process. In the meantime, have a bit of fun with a competitive space invaders game. See if you can get your name to the top of the leaderboard. -
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Laravel Orchid Icons
Simple, minimal line, and clean icon pack in vector formats
...In order to include an icon from a popular icon set such as Font Awesome, you can create a new directory for storing the icons. Once you have created the new directory, you can download the appropriate icons and place them in the new directory. For example, you can download the notebook icon and place it in the fontawesome subdirectory. -
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HiPlot
HiPlot makes understanding high dimensional data easy
HiPlot is an interactive visualization toolkit for exploring high-dimensional experiments, especially those produced during hyperparameter search or ablation studies. Its core view is a parallel-coordinates plot that lets you brush, filter, and highlight runs to spot trade-offs, correlations, and Pareto fronts at a glance. You can load results from simple CSV/JSON logs or programmatically push “experiments” with typed fields, metrics, and tags. The UI supports dynamic filtering, color... -
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gpt-2-simple
Python package to easily retrain OpenAI's GPT-2 text-generating model
...For finetuning, it is strongly recommended to use a GPU, although you can generate using a CPU (albeit much more slowly). If you are training in the cloud, using a Colaboratory notebook or a Google Compute Engine VM w/ the TensorFlow Deep Learning image is strongly recommended. (as the GPT-2 model is hosted on GCP) You can use gpt-2-simple to retrain a model using a GPU for free in this Colaboratory notebook, which also demos additional features of the package. Note: Development on gpt-2-simple has mostly been superceded by aitextgen, which has similar AI text generation capabilities with more efficient training time. -
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SneakGAN
StyleGAN2-ADA trained on a dataset of 2000+ sneaker images
StyleGAN2-ADA trained on a dataset of 2000+ sneaker images. This model was inspired by 98mprice's StyleGAN model and uses the same training data. -
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Deep-Learning-with-TensorFlow-book
Open source Deep Learning book, based on TensorFlow
...It combines theory with practical examples, making it suitable for beginners who want to learn deep learning through hands-on code. The repository includes the PDF book, companion source code, course slides, and notebook-style materials. It covers core machine learning and deep learning concepts through TensorFlow-based implementation. The project also supports educational use, with materials that can be adopted by students, self-learners, and instructors. Overall, it is a complete learning package for understanding modern deep learning workflows through TensorFlow 2.0 examples. -
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Jupyter Dock
Perform molecular docking protocols interactively
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results. These notebooks are Python 3 compatible. Each protocol and Jupyter notebook has its own test folder for testing and reproducibility evaluation. For all notebooks, the demonstration includes the use of AutoDock Vina and Ledock. When available, some alternatives are mentioned in the protocol. Jupyter Dock's initial goal was to provide a set of pythonic protocols for molecular docking. Nonetheless, there is a dearth of docking tools in Python for all of the steps and protocols (i.e. pocket search for blind docking). ... -
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python-tutorial
Practical Python tutorials, including Python basics
...The project is intended for beginners learning Python and for working developers who want reference implementations for common scripts. Its examples are tested in a Python 3 environment and organized into topic-based directories. The repository also includes notebook-style learning materials for basic data types and core language concepts. It is useful as a structured self-study resource, classroom supplement, or quick reference for practical Python usage. -
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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...
