deep_learning_and_the_game_of_go | Code other material for the book `` Deep Learning | Machine Learning library

 by   maxpumperla Python Version: Current License: No License

kandi X-RAY | deep_learning_and_the_game_of_go Summary

kandi X-RAY | deep_learning_and_the_game_of_go Summary

deep_learning_and_the_game_of_go is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. deep_learning_and_the_game_of_go has no bugs, it has no vulnerabilities and it has medium support. However deep_learning_and_the_game_of_go build file is not available. You can install using 'pip install deep_learning_and_the_game_of_go' or download it from GitHub, PyPI.

Code and other material for the book "Deep Learning and the Game of Go"
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            kandi-support Support

              deep_learning_and_the_game_of_go has a medium active ecosystem.
              It has 871 star(s) with 361 fork(s). There are 71 watchers for this library.
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              It had no major release in the last 6 months.
              There are 47 open issues and 37 have been closed. On average issues are closed in 39 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of deep_learning_and_the_game_of_go is current.

            kandi-Quality Quality

              deep_learning_and_the_game_of_go has no bugs reported.

            kandi-Security Security

              deep_learning_and_the_game_of_go has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              deep_learning_and_the_game_of_go does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              deep_learning_and_the_game_of_go releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              deep_learning_and_the_game_of_go has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed deep_learning_and_the_game_of_go and discovered the below as its top functions. This is intended to give you an instant insight into deep_learning_and_the_game_of_go implemented functionality, and help decide if they suit your requirements.
            • Return a Flask application
            • Returns the coordinates of a point
            • Generate an experience
            • Create a temporary file
            • Select a move from the given game state
            • Generate a random position from a set of values
            • Rank moves using a greedy algorithm
            • Predict for a given game state
            • Place a stone
            • Removes a string from the Sudoku
            • Performs self - play
            • Selects a move from the given game state
            • Generate a random rank based on the given values
            • Select a move in the tree
            • Prepare training data
            • Build an alphago model
            • Select a move according to the given state
            • Select a random move
            • Train training data
            • Serialise the node as a string
            • Play multiple games
            • Interpret a list of coordinates
            • Parse a SGF collection
            • Calculate the ratio of agents
            • Do self - play
            • Select the best possible move
            • Reparent this node to another parent
            Get all kandi verified functions for this library.

            deep_learning_and_the_game_of_go Key Features

            No Key Features are available at this moment for deep_learning_and_the_game_of_go.

            deep_learning_and_the_game_of_go Examples and Code Snippets

            No Code Snippets are available at this moment for deep_learning_and_the_game_of_go.

            Community Discussions

            Trending Discussions on deep_learning_and_the_game_of_go

            QUESTION

            How to fix Unresolved import PyDev in Eclipse
            Asked 2019-Feb-01 at 12:38

            I am reading Deep Learning and the Game of Go. I am new to Python. I have an eclipse python project with a folder dlgo. I have an empty init.py in dlgo/. Two other files are in dlgo/: gotypes.py and goboard_slow.py (please see below).

            the statements: from dlgo.gotypes import Player in goboard_slow.py get an: Unresolved import: Player goboard_slow.py /py1/dlgo line 3 PyDev Problem

            This code is from their GitHub site. I just copied the two files into dlgo/ in my project.

            The python path has the project directory as well as dlgo/. Other files that import Player (or Point) have the same problem.

            gotypes.py:

            ...

            ANSWER

            Answered 2019-Feb-01 at 12:38

            It seems like a problem in the folders you're setting as source folders.

            At http://www.pydev.org/faq.html#PyDevFAQ-HowdoIimportexistingprojects/sourcesintoPyDev? there's an explanation on which folders should be set as source folders for things to be found.

            In particular, if you have an import as: from dlgo.gotypes import Player, you should have:

            Source https://stackoverflow.com/questions/54471519

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install deep_learning_and_the_game_of_go

            You can install using 'pip install deep_learning_and_the_game_of_go' or download it from GitHub, PyPI.
            You can use deep_learning_and_the_game_of_go like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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