Udemy - K-Means For Cluster Analysis And Unsupervised Learning In R

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Udemy - K-Means for Cluster Analysis and Unsupervised Learning in R

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Udemy - K-Means for Cluster Analysis and Unsupervised Learning in R.torrent
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Uploaded on 27-11-2020 by our crawler pet called "Spidey".
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Description

[ DevCourseWeb.com ] K-Means for Cluster Analysis and Unsupervised Learning in R



Download More  Courses Visit and Support Us -->> https://DevCourseWeb.com







Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz

Language: English | VTT | Size: 1.05 GB | Duration: 3h 2m

What you'll learn

Understand unsupervised learning and clustering using R-programming language

It covers both theoretical background of K-means clustering analysis as well as practical examples in R and R-Studio

Fully understand the basics of Machine Learning, Cluster Analysis & Unsupervised Machine Learning

How the K-Means algorithm is defined mathematically and how it is derived.

How to implement K-Means very fast with R coding: examples of real data will be provided

How the K-Means algorithm works in general. Get an intuitive explanation with graphics that are easy to understand

Different types of K-meas; Fuzzy K-means, Weighted K-means and visualization of K-Means results in R

Evaluate Model Performance & Learn The Best Practices For Evaluating Machine Learning Model Accuracy

Implementing the K-Means algorithm in R from scratch. Get a really profound understanding of the working principle



Requirements

Availabiliy computer and internet

R-programming skills is NOT a requirement, but would be a plus

Description

Learn why and where K-Means is a powerful tool



Clustering is a very important part of machine learning. Especially unsupervised machine learning is a rising topic in the whole field of artificial intelligence. If we want to learn about cluster analysis, there is no better method to start with, than the k-means algorithm.



Unlike other courses, it offers NOT ONLY the guided nstrations of the R-scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY UNSUPERVISED MACHINE LEARNING (K-means) in R.



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We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...



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