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Clustering and Classification with Machine Learning in R

You're reading from Clustering and Classification with Machine Learning in R The underlying patterns in your data hold vital insights; unearth them with cutting-edge clustering and classification techniques in R

Product type Video

Published in Nov 2019

Publisher Packt

ISBN-13 9781838984571

Length 7hrs 42mins

Edition 1st Edition

Languages

R

Tools

RStudio

Concepts

Machine Learning

Author (1):

Minerva Singh

View More author details

Table of Contents (10) Chapters

1. Introduction to the Course FREE CHAPTER

2. Read in Data from Different Sources in R

3. Data Pre-processing and Visualization

4. Machine Learning for Data Science

5. Unsupervised Learning in R

6. Feature/Dimension Reduction

7. Feature Selection to Select the Most Relevant Predictors

8. Supervised Learning Theory

9. Supervised Learning: Classification

10. Additional Lectures

Fuzzy C-Means Clustering

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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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