Showing 100 open source projects for "python code"

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  • 1
    IPython

    IPython

    Command shell for interactive computing in multiple languages

    IPython provides a rich toolkit to help you make the most of using Python interactively. Comprehensive object introspection. IPython provides input history, persistent across sessions. Caching of output results during a session with automatically generated references. Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. Extensible system of ‘magic’ commands for controlling the environment and performing many...
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  • 2
    pytorch-tutorial

    pytorch-tutorial

    PyTorch Tutorial for Deep Learning Researchers

    pytorch-tutorial is a highly popular educational repository that teaches deep learning with PyTorch through step-by-step examples and well-structured lessons. It is designed primarily for beginners and intermediate practitioners who want to understand PyTorch fundamentals and quickly move toward building real neural network models. The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer...
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  • 3
    This project is intended to provide code to be used with MySQL and Python to create a database of major league baseball game events which are freely provided by the mlb.com Gameday application. Older version also support creating a retrosheet.org database but that is no longer supported. All major and minor league pitch location and game statistic data can be downloaded using BBOS.
    Downloads: 1 This Week
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  • 4
    Think Bayes

    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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  • 5
    Tensorflow and deep learning

    Tensorflow and deep learning

    A crash course in six episodes for software developers

    Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights,...
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  • 6
    Python4Proteomics Course

    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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  • 7
    Data Science at the Command Line

    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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  • 8
    Spinning Up in Deep RL

    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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  • 9
    Neural MMO

    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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  • 10
    Pydicom by examples

    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/
    Downloads: 0 This Week
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  • 11
    CasADi
    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.
    Downloads: 21 This Week
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  • 12
    Evolution Strategies Starter

    Evolution Strategies Starter

    Code for the paper "Evolution Strategies.."

    evolution-strategies-starter is an archived OpenAI research project that provides a distributed implementation of the algorithm described in the paper “Evolution Strategies as a Scalable Alternative to Reinforcement Learning” by Tim Salimans, Jonathan Ho, Xi Chen, and Ilya Sutskever. The repository demonstrates how to scale Evolution Strategies (ES) for reinforcement learning tasks using a master-worker architecture, where the master node broadcasts parameters to multiple workers, and the...
    Downloads: 1 This Week
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  • 13
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  • 14
    stanford-tensorflow-tutorials

    stanford-tensorflow-tutorials

    This repository contains code examples for the Stanford's course

    This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1.
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  • 15
    Python Cookbook

    Python Cookbook

    Python Cookbook, 3rd edition translation

    ...All the code in the book was written and tested under Python 3.3 version. We hope this book will guide people to use Python 3 to write new code or upgrade legacy code.
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  • 16
    PyTorch Book

    PyTorch Book

    PyTorch tutorials and fun projects including neural talk

    This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested...
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  • 17
    A Whirlwind Tour of Python

    A Whirlwind Tour of Python

    The Jupyter Notebooks behind my OReilly report

    ...The material is aimed at people who already know how to program in another language and want to transition efficiently into idiomatic Python, particularly for research and analytical work. Each notebook mixes short explanations with executable code cells, encouraging readers to run, modify, and experiment with examples as they go. The project also backs a free O’Reilly report and an online version of the book, making it easy to read in the browser or work locally with the notebooks.
    Downloads: 0 This Week
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  • 18
    Learning to Learn in TensorFlow

    Learning to Learn in TensorFlow

    Learning to Learn in TensorFlow

    Learning to Learn, created by Google DeepMind, is an experimental framework that implements meta-learning—training neural networks to learn optimization strategies themselves rather than relying on manually designed algorithms like Adam or SGD. The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a...
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  • 19
    TensorFlow World

    TensorFlow World

    Simple and ready-to-use tutorials for TensorFlow

    This repository aims to provide simple and ready-to-use tutorials for TensorFlow. The explanations are present in the wiki associated with this repository. There are different motivations for this open source project. TensorFlow (as we write this document) is one of / the best deep learning frameworks available. The question that should be asked is why has this repository been created when there are so many other tutorials about TensorFlow available on the web? Deep Learning is in very high...
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  • 20
    Python Machine Learning book

    Python Machine Learning book

    The book code repository and info resource

    What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning. From theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. This is not...
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  • 21
    Convolution arithmetic

    Convolution arithmetic

    A technical report on convolution arithmetic in deep learning

    A technical report on convolution arithmetic in the context of deep learning. The code and the images of this tutorial are free to use as regulated by the licence and subject to proper attribution. The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory. We introduce a guide to help deep learning practitioners understand and manipulate convolutional neural network architectures....
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  • 22
    JDFeditor

    JDFeditor

    GUI application for editing database files.

    The purpose is to be a cross-platform, quick and simple database manager, main goal is to provide developers with a tool to produce small to medium size databases efficiently. If you need a database at its simplest form, without any extra hassle of knowing how to access the produced library. Then JDFeditor is the right tool for you. JDFeditor is bundled with an easy-to-use Python library: jdf_lib. jdf_lib will quickly load the content of your database into a variable. All you need...
    Downloads: 1 This Week
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  • 23
    In programming assignments, students tend to copy from one another as they are given the same set of questions. This conduct should not be allowed as it is an individual assignment and each student must complete on his own. The existing program is available to detect plagiarism through source code similitude. However, it is hard to detect similarity in source code especially if the number of students is high. Furthermore, it is better to prevent plagiarism before it is committed. The...
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  • 24
    Matplotlib tutorial

    Matplotlib tutorial

    Matplotlib tutorial for beginner

    ...As the tutorial builds progressively, learners can gradually advance from simple static plots to more complex visualizations, learning how to control figure size, add multiple subplots, adjust plot aesthetics, and handle different data types. Because it is code-first, users can copy, modify, and run the examples on their own datasets, encouraging experimentation and deepening understanding.
    Downloads: 0 This Week
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  • 25
    fPotencia

    fPotencia

    Power flow library in C++

    ...Since Power system simulations have started needing to be executed in parallel, the old C-like designs are outdated; modular design is now needed to launch many simulations at the same time based on a base circuit. fPotencia is programmed in C++, but my intention is to bring JAVA, C#, Python and perhaps MATLAB versions of it. All of them in native code and whenever possible with the same modular structure.
    Downloads: 0 This Week
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