WORKSHOP BIG
DATA ANLYTICS
USING R
MACHINE LERNING
BIG DATA CONCEPT
☐ Exploring the data – Feature
transformation techniques (Z-score, Minmax , log, scale)
☐ Show and Tell of HDFS: Basic commands
and operations
☐ Feature Reduction Techniques (PCA)
☐ Practice on Functions Creation and
Concept of Map-Reduce
☐ Basics of the Language
☐ Big Data Ecosystem
☐ Feature Selection Technique forward and
backward selection
☐ Clustering Technique: Finding the number ☐ Map Reduce Basic Program
of clusters, Metrics, Dimensionality
Reduction with K-mean
☐ Association mining/ Aprori
☐ Basic Functions of Map Reduce
☐ Predictive Model Artifiical Neural Network ☐ Sentiment Analysis using Map Reduce
☐ SVM
☐ Case study discussion and Map Reduce
/Hive
☐ A Case Study Iris, Survey, Sentiment
Analysis of Tweets
☐ Query Sessions
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