Machine-Learning-Note | 机器学习笔记

by lcatro Python Version: Current License: No License

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

kandi X-RAY | Machine-Learning-Note Summary

Machine-Learning-Note is a Python library. Machine-Learning-Note has no vulnerabilities and it has low support. However Machine-Learning-Note has 2 bugs and it build file is not available. You can download it from GitHub.

机器学习笔记

Support

Quality

Security

License

Reuse

Support

Machine-Learning-Note has a low active ecosystem.

It has 413 star(s) with 114 fork(s). There are 18 watchers for this library.

It had no major release in the last 6 months.

Machine-Learning-Note has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Machine-Learning-Note is current.

Quality

Machine-Learning-Note has 2 bugs (2 blocker, 0 critical, 0 major, 0 minor) and 43 code smells.

Security

Machine-Learning-Note has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Machine-Learning-Note code analysis shows 0 unresolved vulnerabilities.

There are 17 security hotspots that need review.

License

Machine-Learning-Note 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

Machine-Learning-Note releases are not available. You will need to build from source code and install.

Machine-Learning-Note 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.

Machine-Learning-Note saves you 233 person hours of effort in developing the same functionality from scratch.

It has 568 lines of code, 47 functions and 11 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Fuzz fuzzing function
Traces a node in the search tree
Add a node to the fuzzing decision tree
Check if a node exists
Compute the model of the model
Return a list of the values in a given data set
Calculates the probability of all occurrences of a given feature
Loads the sample data
Convert image to pixel array
Load an image
Load captcha file
Preprocess the captcha
Test if the given buffer is valid
Decrypt a byte string
Make a picture
Preprocess the image
Try to classify the model
Create the model
Return node data

Get all kandi verified functions for this library.

Machine-Learning-Note Key Features

No Key Features are available at this moment for Machine-Learning-Note.

Machine-Learning-Note Examples and Code Snippets

No Code Snippets are available at this moment for Machine-Learning-Note.

Community Discussions

No Community Discussions are available at this moment for Machine-Learning-Note.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install Machine-Learning-Note

You can download it from GitHub.
You can use Machine-Learning-Note 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 .

Find more information at: