Another exquisit release
Packt.Clustering.and.Classification.with.Machine.Learning.in.R-XQZT
Title: Clustering and Classification with Machine Learning in R
Publisher: Packt
Size: 1.4G (1434662020 B)
Files: 6F
Date: 11/28/2019
Course #: 9781838984571
Type: N/A
Published: 28 Nov 2019
Modified: N/A
URL: www.packtpub.com/data/clustering-and-classification-with-machine-learning-in-r-video
Author: N/A
Duration: 7 hours 42 minutes
Skill: N/A
Exer/Code: [X]
Installation:
Unpack that shit, run that shit
Description:
This course is your complete guide to both supervised and
unsupervised learning using R. This course covers all the main
aspects of practical data science; if you take this course, there is
no need to take other courses or buy books on R-based data
science. In this age of big data, companies across the Globe use R
to sift through the avalanche of information at their
disposal. By becoming proficient in unsupervised and
supervised learning in R, you can give your company a
competitive edge and take your career to the next level.
Over the
course of research, the author realized that almost all the R data
science courses and books out there do take account of the
multidimensional nature of the topic. This course will give you a
robust grounding in the main aspects of machine learning:
clustering and classification. Unlike other R instructors, the
author digs deep into R's machine learning features and give you a
one-of-a-kind grounding in data science! You will go all the way
from carrying out data reading & cleaning to machine
learning, to finally implementing powerful machine learning
algorithms and evaluating their performance via R.
The
following topics will be covered: - • A full introduction to the R
Framework for data science • Data structures and reading in R,
including CSV, Excel, and HTML data • How to pre-process and
clean data by removing NAs/No data, visualization • Machine
learning, supervised learning, and unsupervised learning in R •
Model building and selection and much more!
The course will help
you implement methods using real data obtained from different
sources. Many courses use made-up data that does not empower
students to implement R-based data science in real life. After
taking this course, you'll easily use data science packages such as
Caret to work with real data in R. You'll even understand
concepts such as unsupervised learning, dimension reduction, and
supervised learning. All the code and supporting files for this
course are available at -