Practical Recommender Systems
| Price | $39.99 - $70.95
|
| Rating |  |
| Author | Kim Falk |
| Publisher | Manning |
| Published | 2019 |
| Pages | 432 |
| Language | English |
| Format | Paper book / ebook (PDF) |
| ISBN-10 | 1617292702 |
| ISBN-13 | 9781617292705 |
Online recommender systems help users find movies, jobs, restaurants - even romance! There's an art in combining statistics, demographics, and query terms to achieve results that will delight them. Learn to build a recommender system the right way: it can make or break your application!
Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions. Recommender systems are practically a necessity for keeping your site content current, useful, and interesting to your visitors.
Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you'll encounter as your site grows.
- Kim Falk
5 5 75
Similar Books
by Pramod Singh
Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along with natural language processing and reco...
Price: $20.41 | Publisher: Apress | Release: 2019
Machine Learning with PySpark, 2nd Edition
by Pramod Singh
Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems.Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the...
Price: $49.05 | Publisher: Apress | Release: 2022
Pro Machine Learning Algorithms
by Kishore Ayyadevara
Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a ...
Price: $37.99 | Publisher: Apress | Release: 2018
Data Science from Scratch, 2nd Edition 
by Joel Grus
To really learn data science, you should not only master the tools - data science libraries, frameworks, modules, and toolkits - but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scra...
Price: $22.31 | Publisher: O'Reilly Media | Release: 2019
by Nick Pentreath
Apache Spark is a framework for distributed computing that is designed from the ground up to be optimized for low latency tasks and in-memory data storage. It is one of the few frameworks for parallel computing that combines speed, scalability, in-memory processing, and fault tolerance with ease of programming and a flexible, expressive, ...
Price: $34.99 | Publisher: Packt Publishing | Release: 2015
Building a Recommendation System with R
by Suresh K. Gorakala, Michele Usuelli
A recommendation system performs extensive data analysis in order to generate suggestions to its users about what might interest them. R has recently become one of the most popular programming languages for the data analysis. Its structure allows you to interactively explore the data and its modules contain the most cutting-edge technique...
Price: $29.99 | Publisher: Packt Publishing | Release: 2015
Hands-On Machine Learning on Google Cloud Platform
by Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier
Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions.This book is focused on making the most ...
Price: $44.99 | Publisher: Packt Publishing | Release: 2018
TensorFlow Machine Learning Projects
by Ankit Jain, Armando Fandango, Amita Kapoor
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits - simplicity, efficiency, and flexibility - of using TensorFlow in various real-world projects. With the help of this book, you'll not only learn how to build advanced projects using different...
Price: $34.99 | Publisher: Packt Publishing | Release: 2018