Search Results for "python code editor" - Page 2
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Showing 96 open source projects for "python code editor"
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Python Data Science Handbook
Python Data Science Handbook: full text in Jupyter Notebooks
The Python Data Science Handbook is a comprehensive collection of Jupyter notebooks written by Jake VanderPlas covering fundamental Python libraries for data science, including IPython, NumPy, Pandas, Matplotlib, Scikit-Learn and more. The project is designed for data scientists, researchers, and anyone transitioning into Python-based data work; it assumes you already know basic Python and focuses more on how to use the ecosystem effectively. -
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ThinkJulia.jl
Port of the book Think Python to the Julia programming language
...By combining clear explanations with practical examples, the project helps both beginners and experienced programmers transition to Julia. The material emphasizes not only writing code but also reasoning about algorithms and problem-solving. Since it is freely available, learners and educators can use, adapt, and contribute to the content, making it a valuable resource for self-study or classroom use. -
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The Art of Programming
A collection of practical tips can be found at the bottom of this page
The Art of Programming (Second Edition) is a curated collection of programming problems and solutions originally derived from the Microsoft 100 Interview Questions blog series, later refined into a long-running tutorial and ultimately a published book. Created by July, the series began in 2010 and has since evolved into an in-depth exploration of algorithmic thinking, data structures, and coding interview preparation. The repository brings together 42 classic programming problems from the... -
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Automated_Quiz
A Shell Script for Quizzing the whole class of students and log result
Please download the above zip file and extract it to a secret folder and run the quiz.sh script from that folder in your terminal program, as shown in the youtube videos : https://youtu.be/kQi0XlIaT9M and https://youtu.be/prwKN5DiFp0 You may change the contents of the quiz.txt file to your liking, while maintaining the format of it. Note: Press Enter/Return key after typing on your Terminal, to proceed to the next step, while testing the quiz.sh script. Also, increase the terminal... -
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HTML Quiz Application With Timer & Point
An Easy to Edit HTML, CSS & JAVASCRIPT QUIZ - For Students & Teachers
Just Download & Extract the Above Zip File provided, then edit the script.js file with a good text / code editor like Sublime Text ( Check Google ) & then save the changes & then view the index.html file on the internet browser. That's all. This is a Browser Based, Cross Platform, Supporting all Operating Systems, Easy Application. If needed, you can change the value of the Timer from 15 seconds to any other value, by Searching & Replacing all occurences of 15 in index.html & script.js files. ... -
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The JavaScript Way
The JavaScript Way book
This repository contains the full source of The JavaScript Way, a beginner-friendly yet comprehensive free online book on JavaScript. It covers fundamentals through to frontend and backend development, built with MkDocs and deployed via Poetry-powered local server. It’s open under Creative Commons, code under MIT. -
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WebEditorWeb
Code editor in single HTML file
Code editor written in a single HTML file that runs on the browser tab. There is no need to install, download a single file and run anywhere. To change the initial configuration, edit the wew.html file in the last lines. * WebEditorWeb use CodeMirror components in code editor. -
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WideW - WebIDEWeb
Web IDE in single HTML file
...There is no need to install, download a single file and run anywhere. To change the initial configuration, edit the widew.html file in the last lines. * Widew use CodeMirror components in code editor. URLs: https://soluc.org/widew https://widew.sourceforge.io -
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DeepMind Educational Resources
DeepMind's repo of educational notebooks for learning AI and research
...The repository provides hands-on, beginner-friendly resources that introduce essential AI concepts through Google Colab notebooks, combining intuitive explanations with executable code. The tutorials cover a broad range of topics—from foundational Python programming and data handling to supervised, unsupervised, and reinforcement learning, as well as graph neural networks and scientific reasoning. Specialized notebooks also explore creative AI applications, language modeling, generative models, and protein folding. ... -
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Hello AI World
Guide to deploying deep-learning inference networks
...In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. ... -
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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The... -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. ... -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing... -
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TemaTres: controlled vocabulary server
Manage, Publish and Share Ontologies, Taxonomies, Thesauri, Glossaries
Web application for management formal representations of knowledge, thesauri, taxonomies and multilingual vocabularies / Aplicación para la gestión de representaciones formales del conocimiento, tesauros, taxonomías, vocabularios multilingües. For the latest version of code: https://github.com/tematres/TemaTres-Vocabulary-Server -
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PH_Playground
Simple solution for testing and documenting short code snippets.
Version 4.0: improved history, error, and view mode handling Version 3.0: JavaScript editing, Quick console, History files for browsing and loading scripts. Version 2.0: CodeMirror functionality, ajax calls. Tired of opening an editor to test short code snippets for functionality, saving the file and then running it in a browser? PH_Playground provides a simple solution on a single browser page. Enter the code to be tested into the "PHP" or "JS" window and press "Run". The result will appear as Rendered or Raw HTML as you choose. In the background the code has been saved to a log file. ... -
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Gato (Graph Animation Toolbox): Animate graph algorithms for example for computing shortest paths, minimal spanning trees, maximum flows or maximal cardinality or weight matchings. Create your own animations using the Animated Data Structures (ADS).
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
...All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. ... -
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FFmpeg libav tutorial
FFmpeg libav tutorial
FFmpeg libav tutorial, learn how media works from basic to transmuxing, transcoding and more. Most of the code in here will be in C but don't worry: you can easily understand and apply it to your preferred language. FFmpeg libav has lots of bindings for many languages like python, go and even if your language doesn't have it, you can still support it through the ffi (here's an example with Lua). We'll start with a quick lesson about what is video, audio, codec and container and then we'll go to a crash course on how to use FFmpeg command line and finally we'll write code, feel free to skip directly to the section Learn FFmpeg libav the Hard Way. ... -
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Think Bayes
Code repository for Think Bayes
ThinkBayes is the code repository accompanying Think Bayes: a book on Bayesian statistics written in a computational style. Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md -
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Data Science at the Command Line
Data science at the command line
Command Line by Jeroen Janssens, published by O’Reilly Media in October 2021. Obtain, scrub, explore, and model data with Unix Power Tools. This repository contains the full text, data, and scripts used in the second edition of the book Data Science at the Command Line by Jeroen Janssens. This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful... -
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Spinning Up in Deep RL
Educational resource to help anyone learn deep reinforcement learning
Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the... -
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Neural MMO
Code for the paper "Neural MMO: A Massively Multiagent Game..."
Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term... -
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Pydicom by examples
Basic and intermediate examples of DICOM library with Jupyter
Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/ -
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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
