[ DevCourseWeb.com ] Regression Analysis for Machine Learning & Predictions in R
Download More Courses Visit and Support Us -->> https://DevCourseWeb.com
Created by Kate Alison, Georg Müller | Published 1/2021 Duration: 3.5 hours | 8 sections | 41 lectures | Video: 1280x720, 44 KHz | 1.2 GB Genre: eLearning | Language: English + Sub Learn Complete Hands-On Regression Analysis in R for Machine Learning, Statistical Analysis & Predictive Modelling in R
What you'll learn Your comprehensive guide to Regression Analysis & supervised machine learning using R-programming language It covers the theory and applications of supervised machine learning with the focus on regression analysis using the R-programming language in R-Studio Implement Ordinary Least Square (or simple linear) regression, Random FOrest Regression, Decision Trees, Logistic regression and others using R Perform model's variable selection and assess regression model's accuracy Build machine learning based regression models and test their performance in R Compare different different machine learning models for regression tasks in R Learn how to select the best statistical & machine learning model for your task Learn when and how machine learning models should be applied Carry out coding exercises & your independent project assignment
Requirements Availabiliy computer and internet & strong interest in the topic Description My course will be your hands-on guide to the theory and applications of supervised machine learning with the focus on regression analysis using the R-programming language. 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 REGRESSION ANALYSIS (Linear Regression, Random Forest, KNN, etc) in R (many R packages incl. caret package will be covered) for supervised machine learning and prediction tasks. This course also covers all the main aspects of practical and highly applied data science related to Machine Learning (i.e. regression analysis). Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based Data Science and Machine Learning domain. \n THIS COURSE HAS 8 SECTIONS COVERING EVERY ASPECT OF MACHINE LEARNING: BOTH THEORY & PRACTISE Fully understand the basics of Regression Analysis & supervised Machine Learning from theory to practice Harness applications of parametric and non-parametric regressions in R Learn how to apply correctly regression models and test them in R Learn how to select the best statistical & machine learning model for your task Carry out coding exercises & your independent project assignment Learn the basics of R-programming Get a copy of all scripts used in the course and MORE
Use Winrar to Extract. And use a shorter path when extracting, such as C: drive
ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)
Download More Courses Visit and Support Us -->> https://DevCourseWeb.com
Get More Tutorials and Support Us -->> https://AppWikia.com
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...
|
udp://opentor.org:2710/announce udp://p4p.arenabg.com:1337/announce udp://tracker.torrent.eu.org:451/announce udp://tracker.cyberia.is:6969/announce udp://9.rarbg.to:2870/announce udp://exodus.desync.com:6969/announce udp://explodie.org:6969/announce udp://tracker.moeking.me:6969/announce udp://tracker.opentrackr.org:1337/announce udp://tracker.tiny-vps.com:6969/announce udp://ipv4.tracker.harry.lu:80/announce http://tracker.foreverpirates.co:80/announce udp://tracker.leechers-paradise.org:6969/announce udp://open.stealth.si:80/announce udp://tracker.internetwarriors.net:1337/announce |