Machine Learning Specialist

This specialization will prepare you for the role of a Machine learning specialist It gives a brief idea of mathematical preliminaries, and gives an introduction to R programming language, which is popular language to do machine learning. Concepts of linear and logistic regression are introduced with examples. Then algorithms like Naive-Bayesian, kNN, decision trees, random forests, and support vector machines are introduced. Enough time is spent on understanding the concept behind each algorithm and examples and case studies are provided

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Data Science with R

Learn R, the most widely used open source analytics tool in the world

An Overview of Analytics and Data Science

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Business Statistics and Application

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An Introduction to R

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Predictive Models and Machine Learning

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Introduction to Machine Learning

Master the fundamentals of Machine Learning

Introduction

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Regression Algorithms

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Classifiers: Bayesian and kNN

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Tree Based Algorithms

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SVM and Improving Performance

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Random Forest

Learn an ensemble learning method for classification and regression by using decision trees

Single Decision Tree

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Rise of Ensemble Method

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Hands-on Session in R on Business Cases

General Boosting & Bagging

Build an ensemble of machine learning algorithms using boosting and bagging methods

Decision Tree Ensembles: Bagging and Boosting

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Case Study: Analysis of Credit Data

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Case Study: The Titanic Accident

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Case Study: Comparing Algorithms

What Do You Get?