Cluster Analysis & Unsupervised Machine Learning in R
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | VTT | Size: 1.52 GB | Duration: 3h 19m
What you'll learn
Your complete guide to unsupervised learning and clustering using R-programming language
It covers both theoretical background of UNSUPERVISED MACHINE LERANING as well as practical examples in R and R-Studio
Fully understand the basics of Machine Learning, Cluster Analysis & Unsupervised Machine Learning
Highly practical data science examples related to unsupervised machine learning and clustering
Be Able To Harness The Power Of R For Practical Data Science
You will have a glimpse on the power of cloud computimg with Google services (i.e. Earth Engine)
It covers a real-world application of K-means clustering for mapping tasks in UAE
Improve your R-programming and JavaScript coding skills
Implement Unsupervised Clustering Techniques Such As k-means Clustering and Hierarchical Clustering
Apply your newly learned skills to your independent project
Evaluate Model Performance & Learn The Best Practices For Evaluating Machine Learning Model Accuracy
Requirements
Availabiliy computer and internet
R-programming skills is NOT a requirement, but would be a plus
Description
HERE IS WHY YOU SHOULD TAKE THIS COURSE:
This course will be your complete guide to unsupervised learning and clustering using R-programming language and JavaScript.
Unlike other courses, it offers NOT ONLY the guided demonstrations of the R-scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY UNSUPERVISED MACHINE LEARNING in R.
This course also covers all the main aspects of practical and highly applied data science related to unsupervised machine learning and clustering techniques. Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based data science domain.
In this age of big data, companies across the globe use R and Google Cloud Computing Services to analyze big volumes of data for business and research. By becoming proficient in unsupervised learning in R, you can give your company a competitive edge and boost your career to the next level. In addition, you will have a chance to test the power of cloud computing with Google services (i.e. Earth Engine) for a real-world application of unsupervised K-means learning for mapping applications.
THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF UNSUPERVISED MACHINE LEARNING: THEORY & PRACTISE
- Fully understand the basics of Machine Learning, Cluster Analysis & Unsupervised Machine Learning from theory to practice
- Harness applications of unsupervised learning (cluster analysis) in R and with Google Cloud Services
- Machine Learning, Supervised Learning, Unsupervised Learning in R
- Complete two independent projects on Machine Learning in R and using Google Cloud Services
- Implement Unsupervised Clustering Techniques (k-means Clustering and Hierarchical Clustering etc)
- and MORE
NO PRIOR R OR STATISTICS/MACHINE LEARNING / R KNOWLEDGE REQUIRED:
You'll start by absorbing the most valuable R Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.
