GDP-Predictor | Non Linear Regression

by srishtipatkar Jupyter Notebook Version: Current License: No License

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kandi X-RAY | GDP-Predictor Summary

GDP-Predictor is a Jupyter Notebook library. GDP-Predictor has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Non Linear Regression Analysis Objectives After completing this lab you will be able to: Differentiate between linear and non-linear regression Use non-linear regression model in Python If the data shows a curvy trend, then linear regression will not produce very accurate results when compared to a non-linear regression since linear regression presumes that the data is linear. Let's learn about non linear regressions and apply an example in python. In this notebook, we fit a non-linear model to the datapoints corrensponding to China's GDP from 1960 to 2014.

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GDP-Predictor has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

GDP-Predictor has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of GDP-Predictor is current.

Quality

GDP-Predictor has no bugs reported.

Security

GDP-Predictor has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

GDP-Predictor 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.

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GDP-Predictor releases are not available. You will need to build from source code and install.

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GDP-Predictor Key Features

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GDP-Predictor Examples and Code Snippets

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Install GDP-Predictor

You can download it from GitHub.

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