This course teaches big ideas in machine learning like how to build and evaluate predictive models. This course provides an intro to clustering in R from a machine learning perspective.This online machine learning course is perfect for those who have a solid basis in R and statistics but are complete beginners with machine learning. You’ll get your first intro to machine learning.After learning the true fundamentals of machine learning, you'll experiment with the techniques that are explained in more detail. By the end, you'll be able to learn and build a decision tree and to classify unseen observations with k-Nearest Neighbors.Also, you'll be acquainted with simple linear regression, multi-linear regression, and k-Nearest Neighbors regression.This course teaches the big ideas in machine learning: how to build and evaluate predictive models, how to tune them for optimal performance, how to preprocess data for better results, and much more.At the end of this course, our machine learning and data science video tutorials, you’ll have a great understanding of all the main principles.Details of the course:Module 01: Basics of R tool In this video, we are going to install r programming with rstudio in Windows Platform.Lab 01 R Installation and Concepts In this lab, we are going to learn about how we can install R Programing in Windows and learn about its several key concepts that are necessary for Programming in R.Video 2_R Programming Concepts In this video, we are going to learn the necessary concepts of RProgramming.Video 3_R Progrming Computations In this tutorial, we will be learning about several mathematical algorithms and computations.Lab 02 R P
Your first steps into machine learning. Understand supervised and unsupervised learning, train your first models, and build intuition for how algorithms learn from data.
Start your journey into tensorflow with foundational concepts and hands-on exercises designed for newcomers.
Start your journey into data science with foundational concepts and hands-on exercises designed for newcomers.
Start your journey into computer vision with foundational concepts and hands-on exercises designed for newcomers.
Learn by building. Apply ML to real datasets through guided projects covering end-to-end pipelines from data cleaning to deployment.
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