The document discusses key concepts in artificial intelligence, machine learning, and deep learning, highlighting their applications and limitations. It provides an overview of Hadoop, its ecosystem, and various use cases, including Netflix and TripAdvisor, demonstrating how data processing and analysis can enhance user experiences. Additionally, it touches on the importance of data warehousing for analytical needs.

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Agenda
 What Is Artificial Intelligence ?
 What Is Machine Learning ?
 Limitations Of Machine Learning
 Deep Learning To The Rescue
 What Is Deep Learning ?
 Deep Learning Applications

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Agenda
Hadoop Introduction
Hadoop Ecosystem
Hadoop Use-cases
Demo

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Hadoop Introduction

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Hadoop Introduction
Hadoop is a framework that allows us to store and process large data sets in parallel and distributed fashion.
Allows to dump any kind of data
across the cluster
Allows parallel processing of the
data stored in HDFS
HDFS (Storage)
YARN
(Processing)

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Hadoop Ecosystem

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Hadoop Ecosystem

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Use-Cases

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Use-Cases
Recommendations
Managing Reviews using
NLP
ISIS Tweet network
Analysis

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NetFlix Use-Case

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NetFlix
Recommendation Engine
80% of views comes from
recommendation
Recommendations are driven by
Machine Learning Algorithms
Continuous A/B Testing

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Transformers
The Item Transformer
➢ Extends Spark ML Transformer
➢ Accepts DMC-12 DataFrame with contextual
information
➢ Transforms DataFrame at the item level

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Processes
Using
DataFrames
Multithread
Model
Training
Distributed
Model
Training

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TripAdvisor Use-Case

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TripAdvisor
➢ Covers almost all parts of the world
➢ One of the best platform for hotel
reviews

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TripAdvisor
Dataset
Generation
Training Application
1 32

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ISIS Tweet Use-Case

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Isis Tweets

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Goals
Social Network
Cluster
Analysis
Keyword
Analysis
Data
Categorization
of Links
Sentiment
Analysis
Timeline View

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ISIS Tweet Analysis
Transforming Data
Filtration
Visualizations

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DEMO
Travel Sector Use-Case

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Travel Sector
Find Top 20 frequently travelled destinations
Top 20 locations people travel from
Top 20 high air revenue destinations

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WebDriver vs. IDE vs. RC
➢ Data Warehouse is like a relational database designed for analytical needs.
➢ It functions on the basis of OLAP (Online Analytical Processing).
➢ It is a central location where consolidated data from multiple locations (databases) are stored.