Machine Learning with R Programming

Machine Learning Introduction

Inbuilt Libraries using R

Data Pre-processing Techniques

Data Handling (Importing and exporting data from various sources)

Capstone Project

Statistical Inference System (Statistics Analysis)

Dimensionality Reduction (Feature Engineering)

Supervised Learning : Regression

Supervised Learning : Classification

Unsupervised Learning

Associative Rule Learning (ARL) / Recommender Systems

Hidden Markov Models (HMM)

Hidden Markov Models for Discrete Observations

Discrete HMMs using Deep Learning Libraries

HMMs for Continuous Observations

HMMs for Classification

Reinforcement Learning

Text Mining & Natural Language Processing (NLP) : NLP Python Basics

NLP Core

Word2Vec Analysis

NLP - POS(Parts-of-Speech Tagging)

NLP - Implementations

Deep Learning

Model Selection & Boosting Section : Ensemble Models

Business Analytics

Projects