Search icon Close icon
Search icon
0
Cart icon
Close icon
You have no products in your basket yet
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Machine Learning with Scala Quick Start Guide

You're reading from  Machine Learning with Scala Quick Start Guide

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789345070
Pages 220 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Md. Rezaul Karim Md. Rezaul Karim
Profile icon Md. Rezaul Karim
LinkedIn
Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.
See other products by Md. Rezaul Karim
Ajay Kumar N Ajay Kumar N
Profile icon Ajay Kumar N
LinkedIn
Ajay Kumar N has experience in big data, and specializes in cloud computing and various big data frameworks, including Apache Spark and Apache Hadoop. His primary language of choice is Python, but he also has a special interest in functional programming languages such as Scala. He has worked extensively with NumPy, pandas, and scikit-learn, and often contributes to open source projects related to data science and machine learning.
See other products by Ajay Kumar N
View More author details

Table of Contents (9) Chapters

Preface Introduction to Machine Learning with Scala Scala for Regression Analysis Scala for Learning Classification Scala for Tree-Based Ensemble Techniques Scala for Dimensionality Reduction and Clustering Scala for Recommender System Introduction to Deep Learning with Scala Other Books You May Enjoy

Model-based book recommendation system

In this section, we will show how to develop a model-based book recommendation system with the Spark MLlib library. Books and the corresponding ratings were downloaded from this link: http://www2.informatik.uni-freiburg.de/~cziegler/BX/. There are three CSV files:

  • BX-Users.csv: Contains user's demographic data and each user is specified with user IDs (User-ID).

  • BX-Books.csv: Book related information such as Book-Title, Book-Author, Year-Of-Publication, and Publisher are there. Each book is identified by an ISBN. Also, Image-URL-S, Image-URL-M, and Image-URL-L are given.

  • BX-Book-Ratings.csv: Contains the rating specified by the Book-Rating column. Ratings are on a scale from 1 to 10 (higher values denoting higher appreciation), or implicit, expressed by 0.

Before we jump into the coding part, we need to know a bit more about...

lock icon The rest of the chapter is locked
arrow left Previous Chapter
Chapter 1 of 9
Next Chapter arrow right
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Sign up now
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Start free trial
Renews at $15.99/month. Cancel anytime}

Authors (2)

Left arrow icon
Profile icon Md. Rezaul Karim
LinkedIn
Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.
Read more
See other products by Md. Rezaul Karim
Profile icon Ajay Kumar N
LinkedIn
Ajay Kumar N has experience in big data, and specializes in cloud computing and various big data frameworks, including Apache Spark and Apache Hadoop. His primary language of choice is Python, but he also has a special interest in functional programming languages such as Scala. He has worked extensively with NumPy, pandas, and scikit-learn, and often contributes to open source projects related to data science and machine learning.
See other products by Ajay Kumar N
Right arrow icon

Other recommended products

Related to this chapter
Left arrow icon
Scala Machine Learning Projects
Scala Machine Learning Projects
Scala is one of the widely used programming language in the world when it comes to handle large amount of data. With the rise of machine learning, data scientists and machine learning experts do prefer scala as a language in order to handle and scale efficient machine learning applications. You will be acquainted with the popular deep/machine learning libraries for Scala such as Spark ML/MLlib, H2O, DeepLearning4j, MXNET etc., and will use their features to build and deploy projects on a framework such as Apache Spark. By the end of this book, you will be able to dominate numerical computing, deep learning, and functional programming to carry out complex advanced tasks with ease.
Jan 2018 15 hours 40 minutes
Java Deep Learning Projects
Java Deep Learning Projects
You will build full-fledged, deep learning applications with Java and different open-source libraries. Master numerical computing, deep learning, and the latest Java programming features to carry out complex advanced tasks. This book is filled with best practices/tips after every project to help you optimize your deep learning models with ease.
Jun 2018 14 hours 32 minutes
Hands-On Deep Learning for IoT
Hands-On Deep Learning for IoT
This book will provide you an overview of Deep Learning techniques to facilitate the analytics and learning in various IoT apps. We will take you through each process - from data collection, analysis, modeling, statistics, and monitoring. We will make IoT data speak with a set of popular frameworks, like TensorFlow, TensorFlow Lite, and Chainer.
Jun 2019 10 hours 16 minutes
Scala and Spark for Big Data Analytics
Scala and Spark for Big Data Analytics
Over the last few years, Scala has been adopted increasingly, especially in the field of data science and analytics, along with Apache Spark, which is built on Scala and is widely used in the field of analytics. With this book, you’ll learn how to leverage the power of both Scala and Spark to make sense of big data.
Jul 2017 26 hours 32 minutes
Apache Spark 2.x Cookbook
Apache Spark 2.x Cookbook
Apache Spark has become the hottest platform and sought after skill set when it comes to the fields of Big Data, Analytics and Data Science. Apache Spark 2.x comes with series of new improvements in the areas of performance, scalability, operational and production readiness for structured processing of massive datasets. This book brings in a systematic way of getting a practical hands on to using its improved programming APIs, expanded SQL functionalities and implement distributed machine learning applications with Spark ML. Through the course of chapters, you will have explored the power of Spark DataFrames/Datasets, harness MLLib for Data mining, analyze complex problems with iterative or multi-stage Spark scripts and other associated toolsets such as Spark SQL, Spark Streaming and GraphX .
May 2017 9 hours 48 minutes
Hands-On Recommendation Systems with Python
Hands-On Recommendation Systems with Python
Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether it's friends, movies or groceries, goes a long way in defining user experience and enticing your customers to use and buy from your platform. This book teaches you to do just that.
Jul 2018 4 hours 52 minutes
Predictive Analytics with TensorFlow
Predictive Analytics with TensorFlow
Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. Data mining, statistics, and machine learning allow users to discover predictive intelligence by uncovering patterns and showing the relationship between structured and unstructured data. This book will help you build solutions that will make automated decisions. In the end, tune and build your own predictive analytics model with the help of TensorFlow.
Nov 2017 17 hours 24 minutes
Machine Learning with Spark
Machine Learning with Spark
Spark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression.
Apr 2017 17 hours 44 minutes
TensorFlow: Powerful Predictive Analytics with TensorFlow
TensorFlow: Powerful Predictive Analytics with TensorFlow
Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis.
Mar 2018 5 hours 28 minutes
Machine Learning with R Cookbook
Machine Learning with R Cookbook
The R language is a powerful open source functional programming language. At its core, R is a statistical language that provides impressive tools to analyze data and create high-level graphics. This book covers the basics of R by setting up a user-friendly programming environment and programming ETL in R. Data exploration examples are provided that demonstrate how powerful data visualisation and machine learning is in discovering hidden relationships. You will also explore air quality data, steps to fix the missing values and visualising the same. You will then dive into important machine learning topics, including data classification, regression, survival analysis, time series analysis, clustering association rule mining, and dimension reduction.This book will include the latest code and examples based on R 3.3 and above—updated for better computation, accuracy, and speed with R.
Oct 2017 19 hours 4 minutes
Learning Spark SQL
Learning Spark SQL
In the past year, Apache Spark has been increasingly adopted for development of distributed applications. Spark SQL APIs provides an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Understanding the design and implementation best practices for Spark SQL API based applications before you start your project will help you avoid these problems and ensure that your project is a success. Learning Spark SQL gives an insight into the engineering practices used to design and build real-world Spark-based applications. The hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL.
Sep 2017 15 hours 4 minutes
Apache Spark 2.x Machine Learning Cookbook
Apache Spark 2.x Machine Learning Cookbook
Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we’ll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems.
Sep 2017 22 hours 12 minutes
Right arrow icon

Personalised recommendations for you

Based on your interests and search pattern
Left arrow icon
Et al.
Et al.
Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.
Aug 2023 7 hours 40 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Mastering Tableau 2023
Mastering Tableau 2023
This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.
Aug 2023 22 hours 48 minutes
Building AI Applications with ChatGPT APIs
Building AI Applications with ChatGPT APIs
This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.
Sep 2023 8 hours 36 minutes
Building AI Applications with ChatGPT APIs
Building AI Applications with ChatGPT APIs
This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.
Sep 2023 8 hours 36 minutes
Data Engineering with AWS
Data Engineering with AWS
Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.
Oct 2023 21 hours 12 minutes
Modern Data Architecture on AWS
Modern Data Architecture on AWS
Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.
Aug 2023 14 hours 0 minutes
Practical Guide to Applied Conformal Prediction in Python
Practical Guide to Applied Conformal Prediction in Python
Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.
Dec 2023 8 hours 0 minutes
TinyML Cookbook
TinyML Cookbook
With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.
Nov 2023 22 hours 8 minutes
Right arrow icon