Showing 34 open source projects for "rur: a python learning environment"

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  • 1
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more.
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  • 2
    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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  • 3
    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django - Code Samples

    Code samples from the Django tutorial series. I’m starting a new tutorial series about Django fundamentals. It’s a complete beginner’s guide to start learning Django. The material is divided into seven parts. We’re going to explore all the basic concepts in great detail, from installation, and preparation of the development environment, models, views, templates, URLs to more advanced topics such as migrations, testing, and deployment. I wanted to do something different. A tutorial that would be easy to follow, informative and fun to read. ...
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  • 4
    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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  • 5

    CLUE - C Learning Undergrad Environment

    Tools to support the learning of the C programming language

    CLUE (C Learning Undergraduate Environment) is a software allowing students to work on assignments in the C language while benefiting from support for peer testing, hyper-linked tutorials to help them understand compiler error messages, detection of "novice errors" with warnings hyper-linked to tutorials. Sponsored by National Science Foundation under award CCLI #0836863.
    Downloads: 0 This Week
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  • 6

    MarketSim

    A python based auction market simulator for agricultural trade

    The market assumes an environment in which farmers sell their produce through brokers and traders locate produce to buy through brokers. The major aim of the simulator is to experiment with various reputation mechanisms to manage bottlenecks and to model various adversarial scenarios. The market is aimed to simulate agricultural trade in developing countries. It is written in python and mysql database on Linux.
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  • 7
    "Roberge's Used Robot (RUR) : a Python Learning Environment" is a Python implementation of a "robot environment" as introduced by R. Pattis in 1981. **It is obsolete.** See https://github.com/aroberge/rur-ple
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    Downloads: 112 This Week
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  • 8
    An AI sandbox for learning game programming. It includes an integrated development environment, and functionality for rapid development of virtual characters.
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  • 9

    Think Python

    Think Python is an interactive online learning environment for Python.

    Think Python intends to be an interactive online learning environment for Python. It consists of two parts: A small IDE which is able to run your Python code in the browser without installing any plugins and an interactive training system which can contain explainations, questions and practical tasks.
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