mlbook | Example code for the Wiley book | Machine Learning library

by jasebell Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | mlbook Summary

mlbook is a Java library typically used in Artificial Intelligence, Machine Learning applications. mlbook has no bugs, it has no vulnerabilities and it has low support. However mlbook build file is not available. You can download it from GitHub.

Machine Learning - Hands On For Developers and Technical Professionals. All the code covered in the book is here. There’s also a directory with the test data used.

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Quality

Security

License

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Support

mlbook has a low active ecosystem.

It has 61 star(s) with 67 fork(s). There are 11 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 2 have been closed. On average issues are closed in 695 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mlbook is current.

Quality

mlbook has 0 bugs and 0 code smells.

Security

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

mlbook code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

mlbook does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

mlbook releases are not available. You will need to build from source code and install.

mlbook has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed mlbook and discovered the below as its top functions. This is intended to give you an instant insight into mlbook implemented functionality, and help decide if they suit your requirements.

Classifies an instance
Identifier 1 4
This method identifies the numeric value of an integer range
Symmetry 1 4 4
Prints a single country code
Gets the country code for the given country
Returns the global information about this classifier
Returns a human - readable description of this class
Tests the classifier of the training data
Returns the capabilities of this classifier
Transform payload
Compute the sum of the values
Main entry point
Reads recommendations
Show recommendations
Map a single word
Update the stock items
Get the revision string
Run HashtagMiner
Generate a recommendations based on the supplied input string

Get all kandi verified functions for this library.

mlbook Key Features

No Key Features are available at this moment for mlbook.

mlbook Examples and Code Snippets

No Code Snippets are available at this moment for mlbook.

Community Discussions

Trending Discussions on mlbook

Installing Tensorflow 2 gets a dll failed to load in pywrap_tensorflow.py

QUESTION

Installing Tensorflow 2 gets a dll failed to load in pywrap_tensorflow.py

Asked 2020-Jul-26 at 16:09

I have had problems here, here and there installing TensorFlow 2 over the last year or so. So I am trying Miniconda.

I have an AMD Radeon hd 6670 and an AMD Radeon hd 6450.

I just downloaded Miniconda and made an environment and did a pip install --upgrade tensorflow in a Miniconda prompt on Windows 8.1 and got TensorFlow 2.2.

When I try to import tensorflow I get the stack trace below.

I did download Visual Studio to get the latest redistributebles (I think).

seems like this occurs near this line: from tensorflow.python.pywrap_tensorflow_internal import *

Edit 1: I used this yaml file for python 3.6 (the other was 3.7), but it produced the same error.

Edit 2: I upgraded to Conda 4.8.3 and Python 3.7 (in the yaml file) and got the same error. This is the line in pywrap internal that shows the problem:

...

ANSWER

Answered 2020-Jul-26 at 16:09

Status Quo

I ran into a comparable problem (this is the furthest i got) reproducibly on two machines. Some of the discussed issues seems to be known for example here: 1 2 3 4. Not only to reproduce 2, it makes sense to also start using virtual environments in order to test multiple tf versions. This can be achieved like this: (link for virtualenv on windows)

Source https://stackoverflow.com/questions/62376660

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

Vulnerabilities

No vulnerabilities reported

Install mlbook

You can download it from GitHub.
You can use mlbook like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the mlbook component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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