Packt+ | Advance your knowledge in tech

You're reading from Apache Spark 2.x Machine Learning Cookbook

Product typeBook

Published inSep 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781783551606

Edition1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Machine Learning

Authors (5):

Mohammed Guller

Siamak Amirghodsi

Shuen Mei

Meenakshi Rajendran

Broderick Hall

View More author details

Naive Bayes machine learning with Spark 2.0 MLlib

In this recipe, we use the famous Iris dataset and use Spark API NaiveBayes() to classify/predict which of the three classes of flower a given set of observations belongs to. This is an example of a multi-class classifier and requires multi-class metrics for measurements of fit. The previous recipe a binary classification and metric to measure the fit.

How to do it...

For the Naive Bayes exercise, we use a famous dataset called iris.data, which can be obtained from UCI. The dataset was originally introduced in the 1930s by R. Fisher. The set is a multivariate dataset with flower attribute measurements classified into three groups.

In short, by measuring four columns, we attempt to classify a species into one of the three classes of Iris flower (that is, Iris Setosa, Iris Versicolor, Iris Virginica).

We can download the data from here:

https://archive.ics.uci.edu/ml/datasets/Iris/

The column definition is as follows:

- Sepal length in cm
- Sepal width...

The rest of the page is locked

You have been reading a chapter from

Apache Spark 2.x Machine Learning Cookbook

Published in: Sep 2017Publisher: PacktISBN-13: 9781783551606

Authors (5)

Mohammed Guller

Author of Big Data Analytics with Spark - http://www.apress.com/9781484209653
Read more about Mohammed Guller

Siamak Amirghodsi

Siamak Amirghodsi (Sammy) is interested in building advanced technical teams, executive management, Spark, Hadoop, big data analytics, AI, deep learning nets, TensorFlow, cognitive models, swarm algorithms, real-time streaming systems, quantum computing, financial risk management, trading signal discovery, econometrics, long-term financial cycles, IoT, blockchain, probabilistic graphical models, cryptography, and NLP.
Read more about Siamak Amirghodsi

Shuen Mei

Shuen Mei is a big data analytic platforms expert with 15+ years of experience in designing, building, and executing large-scale, enterprise-distributed financial systems with mission-critical low-latency requirements. He is certified in the Apache Spark, Cloudera Big Data platform, including Developer, Admin, and HBase. He is also a certified AWS solutions architect with emphasis on peta-byte range real-time data platform systems.
Read more about Shuen Mei

Meenakshi Rajendran

Meenakshi Rajendran is experienced in the end-to-end delivery of data analytics and data science products for leading financial institutions. Meenakshi holds a master's degree in business administration and is a certified PMP with over 13 years of experience in global software delivery environments. Her areas of research and interest are Apache Spark, cloud, regulatory data governance, machine learning, Cassandra, and managing global data teams at scale.
Read more about Meenakshi Rajendran

Broderick Hall

Broderick Hall is a hands-on big data analytics expert and holds a masters degree in computer science with 20 years of experience in designing and developing complex enterprise-wide software applications with real-time and regulatory requirements at a global scale. He is a deep learning early adopter and is currently working on a large-scale cloud-based data platform with deep learning net augmentation.
Read more about Broderick Hall

Other recommended products

Related to this chapter

Hands-On Big Data Analytics with PySpark

In this book, you'll learn to implement some practical and proven techniques to improve aspects of programming and administration in Apache Spark. Techniques are demonstrated using practical examples and best practices. You will also learn how to use Spark and its Python API to create performant analytics with large-scale data.

BookMar 2019182 pages

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.

BookApr 2017532 pages

Hands-On Data Analysis with Scala

This book will help you perform effective data analysis with Scala using practical examples. You will come across different challenges and their effective solutions for a variety of data processing tasks - be it data exploration, data manipulation, or real-time data analysis using Apache Spark.

BookMay 2019298 pages

Apache Spark Quick Start Guide

Apache Spark is a ?exible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write efficient big data applications for a variety of use cases.

BookJan 2019154 pages

Modern Scala Projects

Scala is a multipurpose programming language, especially for analyzing large datasets without impacting the application performance. Its functional libraries can interact with databases and build scalable frameworks that create robust data pipelines. This book showcases how you can use Scala and its constructs to meet specific project demands.

BookJul 2018334 pages

PySpark Cookbook

This cookbook presents recipes on leveraging the power of Python and putting it to use in the Apache Spark ecosystem. By the end of this book, you will be able to solve any problem associated with building effective, data-intensive applications and performing machine learning and structured streaming using PySpark.

BookJun 2018330 pages

Learning Apache Spark 2

Apache Spark is one of the most popular Big Data processing frameworks today, delivering speed, accuracy and real-time results – all in one solution. With this book, you will delve into the world of Apache Spark and learn about the new features introduced in Spark 2, along with the architecture and the associated concepts. A comprehensive guide to Apache Spark 2 for beginners, this book covers everything you need to know to get up and running with Big Data processing, machine learning and stream processing with Apache Spark, and allows you to easily understand each of these concepts through real-world examples.

BookMar 2017356 pages

Machine Learning with Scala Quick Start Guide

Scala as a programming language is a highly scalable integration of object-oriented and functional programming, which makes it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to train effective machine learning models using this popular language.

BookApr 2019220 pages

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.

BookJul 2017796 pages

Apache Spark 2.x for Java Developers

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.

BookJul 2017350 pages

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.

BookSep 2017452 pages

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 .

BookMay 2017294 pages

Personalised recommendations for you

Based on your interests and search pattern

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.

BookAug 2023230 pages5

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.

BookDec 2023360 pages4

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.

BookDec 2023360 pages5

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.

BookDec 2023360 pages1

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.

BookDec 2023360 pages5

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.

BookAug 2023684 pages

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.

BookSep 2023258 pages5

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.

BookSep 2023258 pages2

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.

BookOct 2023636 pages5

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.

BookAug 2023420 pages5

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.

BookDec 2023240 pages

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.

BookNov 2023664 pages

You're reading from Apache Spark 2.x Machine Learning Cookbook

Naive Bayes machine learning with Spark 2.0 MLlib

How to do it...

Unlock this book and the full library FREE for 7 days

Authors (5)

Hands-On Big Data Analytics with PySpark

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.

Hands-On Data Analysis with Scala

This book will help you perform effective data analysis with Scala using practical examples. You will come across different challenges and their effective solutions for a variety of data processing tasks - be it data exploration, data manipulation, or real-time data analysis using Apache Spark.

Apache Spark Quick Start Guide

Modern Scala Projects

PySpark Cookbook

Learning Apache Spark 2

Machine Learning with Scala Quick Start Guide

Scala and Spark for Big Data Analytics

Apache Spark 2.x for Java Developers

Learning Spark SQL

Apache Spark 2.x Cookbook

Et al.

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.

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.

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.

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.

Mastering Tableau 2023

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

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.

Modern Data Architecture on AWS

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.

TinyML Cookbook