Machine Learning & Predictive Models in R |Theory & Practice

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English + .srt | Duration: 65 lectures (6 hour, 44 mins) | Size: 1.99 GB

What you'll learn

Your complete guide to unsupervised & supervised machine learning and predictive modeling using R-programming language

It covers both theoretical background of MACHINE LERANING & and predictive modeling as well as practical examples in R and R-Studio

Fully understand the basics of Machine Learning, Cluster Analysis & Predictive Modelling

Highly practical data science examples related to supervised machine learning, clustering & prediction modelling in R

Learn R-programming from scratch: R crash course is included that you could start R-programming for machine learning

Be Able To Harness The Power of R For Practical Data Science

Compare different different machine learning algorithms for regression & classification modelling

Apply statistical and machine learning based regression & classification models to real data

Build machine learning based regression & classification models and test their robustness in R

Learn when and how machine learning & predictive models should be correctly applied

Test your skills with multiple coding exercices and final project that you will ommplement independently

Implement Machine Learning Techniques/Classification Such As Random Forests, SVM etc in R

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