Machine Learning Training course

Data Science & Machine Learning     

Introduction to Data Science

• Introduction
• Understanding Big Data
• Understand how different companies use big data for their business need
• Big Data Challanges
• Introduction to Data Science
• Types of Data Scientists
• Data Science Components
• Data Science Use Cases
• Introduction to R and Hadoop
• R and Hadoop Integration
• Machine Learning with Mahout

Hadoop Architecture HDFS & Map Reduce

• HDFS- Hadoop Distributed File System
• Assumptions and Goals
• CAP principle
• Anatomy of Hadoop Cluster
• Anatomy of a File Write
• Anatomy of a File Read
• Map Reduce Framework Architecture
• Hadoop Processes
• Understanding Various configuration Properties of Hadoop

Data Manipulation Using R

• Introduction to R
• Describe why R is Used?
• Implement R programing concepts
• Learn Data Import techniques
• Analyze the processing of the Data

Statistics and Probability

• Observation and Experiments
• Sampling Methods
• Quantitative Variables
• Skewness,Modality and Measures of Centre
• Variance, Standard Deviation, Interquartile Range
• Probability Rules
• Disjoint, Non Disjoint events, Independence
• Conditional Probability
• Probability Distributions

Machine Learning Techniques - Part 1

• Understand Machine Learning
• Use Cases Walkthrough
• Machine Learning Techniques
• Describe Clustering
• Analyze Clustering Scenarios using Clustering Algorithms
• Learn TF-IDF and cosine Similarity

Machine Learning Techniques - Part 2

• Understand Supervised Learning Technique
• Classification
• Recommendation
• Learn Decision Tree Classifier
• Implement how various Decision Tree algorithms work.
• Implement Application of Techniques on a smaller datasets for better understanding using R.

Machine Learning Techniques - Part 3

• Understand Unsupervised Learning Technique
• Understand the implementation of Random Forest Classifier
• Understand the implementation of Na-ve Bayer's Classifier
• Apply both techniques on smaller datasets using R
• Understand Association Rule Mining

Integrating R with Hadoop

• Understand the need for R integration with Hadoop
• Learn the ways to integrate R and Hadoop
• Understand the usage of R Hadoop package
• Perform R integration with Hadoop and Run Map Reduce examples

Mahout Introduction and Algorithm Implementation

• Understand Mahout
• Gain insight on implementing Machine Learning with Mahout
• Understand Learning, Classification and Clustering techniques with Mahout
• Implement Recommendation technique and Frequent Pattern Mining in Mahout

Advanced Mahout Algorithms, Parallel processing and Data      Visualization

   Tableau Introduction

     Building Dashboards

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