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Regression Analysis for Statistics & Machine Learning in R

You're reading from Regression Analysis for Statistics & Machine Learning in R Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Product type Video

Published in Nov 2019

Publisher Packt

ISBN-13 9781838987862

Length 7hrs 18mins

Edition 1st Edition

Languages

R

Tools

RStudio

Concepts

Machine Learning

Author (1):

Minerva Singh

View More author details

Table of Contents (7) Chapters

1. Get Started with Practical Regression Analysis in R FREE CHAPTER

2. Ordinary Least Square Regression Modelling

3. Deal with Multicollinearity in OLS Regression Models

4. Variable & Model Selection

5. Dealing with Other Violations of the OLS Regression Models

6. Generalized Linear Models (GLMs)

7. Working with Non-Parametric and Non-Linear Data

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Authors (1)

Minerva Singh

Minerva Singh

Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.

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