Book Image

Hadoop Blueprints

By : Anurag Shrivastava, Tanmay Deshpande
Book Image

Hadoop Blueprints

By: Anurag Shrivastava, Tanmay Deshpande

Overview of this book

If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.
Table of Contents (14 chapters)
Hadoop Blueprints
About the Authors
About the Reviewers

Building the machine learning model

We will start building a machine learning model with the help of historical data now with the help of BigML.

Introducing BigML

BigML is a web-based tool to build machine learning models from datasets. BigML has several advantages over other machine learning languages such as R and tools such as RapidMiner, such as:

  • No local software installation is required. BigML is a web-based tool.

  • Data processing is done in the cloud, which means you do not have to invest in expensive servers for building the models.

  • No need to learn a new programming language to build models. BigML is a UI-driven tool.

Model building steps

We will go through six simple steps to build a machine learning model as follows:

  1. Register as a user on the BigML site.

  2. Upload the data file.

  3. Create the dataset with the help of the data file.

  4. Build the classification model using the dataset.

  5. Download the classification model.

  6. Run the model using MapReduce on Hadoop for scoring.

We will now explain these steps...