100DaysofMLCode | Machine Learning and Artificial Intelligence | Machine Learning library

by NishkarshRaj Jupyter Notebook Version: Current License: MIT

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

kandi X-RAY | 100DaysofMLCode Summary

100DaysofMLCode is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. 100DaysofMLCode has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

#100DaysofMLCode Challenege

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100DaysofMLCode has a low active ecosystem.

It has 292 star(s) with 150 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 14 open issues and 17 have been closed. On average issues are closed in 69 days. There are 19 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of 100DaysofMLCode is current.

Quality

100DaysofMLCode has 0 bugs and 0 code smells.

Security

100DaysofMLCode has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

100DaysofMLCode code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

100DaysofMLCode is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

100DaysofMLCode releases are not available. You will need to build from source code and install.

100DaysofMLCode saves you 731 person hours of effort in developing the same functionality from scratch.

It has 1687 lines of code, 64 functions and 40 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed 100DaysofMLCode and discovered the below as its top functions. This is intended to give you an instant insight into 100DaysofMLCode implemented functionality, and help decide if they suit your requirements.

Estimates missing values in the dataset
Applies a linear regression
Create a new matrix with no missing data
Generates the predicted targets using the best fit method
Preprocess the data
Train and test function
Splits the dataset
Calculate the accuracy of the prediction
Perform a apriori algorithm
Create a TransactionManager instance
Generate support records
Calculate the support for the given items
Visualize the classification
Generate ordered statistics

Get all kandi verified functions for this library.

100DaysofMLCode Key Features

No Key Features are available at this moment for 100DaysofMLCode.

100DaysofMLCode Examples and Code Snippets

No Code Snippets are available at this moment for 100DaysofMLCode.

Community Discussions

Trending Discussions on 100DaysofMLCode

Is it possible to put a readme file for R code on github, that displays output?

QUESTION

Is it possible to put a readme file for R code on github, that displays output?

Asked 2018-Aug-21 at 23:32

Recently I participated in the #100daysofmlcode challenge on Linkedin, started by Siraj Raval. I do all of my coding in R. But when I push an RMarkdown file or readme file for my rcode, on Github, it doesn't show the output generated from the code. This makes it really difficult for viewers to catch up with the explanation. Is there a way we could display the code and output, so that it becomes easier for readers to understand? I know they can pull the changes I make from github and see them on their local machines. But considering the time limitations that everyone has, I would still like to know if there is a way we can display both Rcode and output in a readme file on github.

Thank you

...

ANSWER

Answered 2018-Aug-21 at 23:28

In markdown, you use ` ` for inline code and ``` ``` for blocks (multiple lines) of code

Source https://stackoverflow.com/questions/51957921

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