Home Page Icon
Home Page
Table of Contents for
Cover
Close
Cover
by Saleem Ansari
Building a Recommendation Engine with Scala
Building a Recommendation Engine with Scala
Table of Contents
Building a Recommendation Engine with Scala
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Introduction to Scala and Machine Learning
Setting up Scala, SBT, and Apache Spark
A quick introduction to Scala
Case classes
Tuples
Scala REPL
SBT – Scala Build Tool
Apache Spark
Setting up a standalone Apache Spark cluster
Apache Spark – MLlib
Machine learning and recommendation engines
Summary
2. Data Processing Pipeline Using Scala
Entree – a sample dataset for recommendation systems
Data analysis of the Entree dataset
ETL – extract transform load
Extract
Transform
Load
Extraction and transformation for machine learning
Types of data
Discrete
Continuous
Categorical
Cleaning the data
Missing data
Normalization
Standardization
Setting up MongoDB and Apache Kafka
Setting up MongoDB
Setting up Apache Kafka
Data processing pipeline for Entree
How does it relate to information retrieval?
Summary
3. Conceptualizing an E-Commerce Store
Importance of recommender systems in e-commerce
Converting browsers into buyers
Making cross-sell happen
Increased loyalty time
Types of recommendation methods
Frequently bought together
An example of frequent patterns
People to people correlation
Customer reviews and ratings
People who were also interested in other similar items
Recommendation from others' views
Example of similar items
Manual
Automatic
Ephemeral
Persistent
The architecture of the project
Batch versus online
Summary
4. Machine Learning Algorithms
Hands on with Spark/MLlib
Data types
Vector
Matrix
Labeled point
Statistics
Summary statistics
Correlation
Sampling
Hypothesis testing
Random data generation
Feature extraction and transformation
Term frequency-inverted document frequency (TF-IDF)
Word2Vec
StandardScaler
Normalizer
Feature selection
Dimensionality reduction
Classification/regression
Linear methods
Naive Bayes
Decision trees
Ensembles
Clustering
K-Means
Expectation-maximization
Power iteration clustering
Latent Dirichlet Allocation
LDA example
Association analysis
Frequent pattern mining (FPGrowth)
Summary
5. Recommendation Engines and Where They Fit in?
Populating the Amazon dataset
Creating a web app with user/product pages
Creating a Play framework application
The home page
Product Groups
Product view
Customer views
Adding recommendation pages
The Top Rated view
The Most Popular view
The Monthly Trends view
Summary
6. Collaborative Filtering versus Content-Based Recommendation Engines
Content-based recommendation
Similarity measures
Pearson correlation
Challenges with Pearson correlation
Euclidean distance
Challenges with Euclidean distance
Cosine measure
Spearman correlation
Tanimoto coefficient
Log likelihood test
Content-based recommendation steps
Clustering for performance
Collaborative filtering based recommendation
What is ALS?
ALS in Apache Spark
ALS on Amazon ratings
Content-based versus collaborative filtering
Summary
7. Enhancing the User Experience
Adding product search
Setting up Elasticsearch
Adding recommendation listings
Understanding recommendation behavior
Why is that so?
Logging
Ranking
Diversification
Justification
Evaluation
Summary
8. Learning from User Feedback
Introducing PredictionIO
Installing PredictionIO
Unified recommender
Summary
Index
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Next
Next Chapter
Table of Contents
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset