MachineLearningWithMe | repository contains more than 10 common statistical machine

by moon-hotel Python Version: version1.0 License: No License

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

kandi X-RAY | MachineLearningWithMe Summary

MachineLearningWithMe is a Python library. MachineLearningWithMe has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

《跟我一起机器学习》

Support

Quality

Security

License

Reuse

Support

MachineLearningWithMe has a low active ecosystem.

It has 134 star(s) with 27 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

MachineLearningWithMe has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MachineLearningWithMe is version1.0

Quality

MachineLearningWithMe has no bugs reported.

Security

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

License

MachineLearningWithMe 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

MachineLearningWithMe releases are available to install and integrate.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

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

Visualize an O visualization .
The SMO optimizer .
Generates the initial center of the points x
takes a string and vectorize it with frequency
searize a string
function to plot contour
Visualize kmeanspp .
Plot a 3D contour
Load and cut the data from the data directory .
Plot the surface and jump points .

Get all kandi verified functions for this library.

MachineLearningWithMe Key Features

No Key Features are available at this moment for MachineLearningWithMe.

MachineLearningWithMe Examples and Code Snippets

No Code Snippets are available at this moment for MachineLearningWithMe.

Community Discussions

No Community Discussions are available at this moment for MachineLearningWithMe.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install MachineLearningWithMe

You can download it from GitHub.
You can use MachineLearningWithMe 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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