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Hands-On Machine Learning with IBM Watson

Hands-On Machine Learning with IBM Watson

By : James D. Miller
1 (1)
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Hands-On Machine Learning with IBM Watson

Hands-On Machine Learning with IBM Watson

1 (1)
By: James D. Miller

Overview of this book

IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples.
Table of Contents (15 chapters)
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Section 1: Introduction and Foundation
6
Section 2: Tools and Ingredients for Machine Learning in IBM Cloud
10
Section 3: Real-Life Complete Case Studies

To get the most out of this book

A basic knowledge of Python and a limited understanding of machine learning will be beneficial.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packt.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-IBM-Watson. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "The file we are using in this project (combine.csv) is a comma-delimited text file containing statistics on players who attended the NFL scouting combine."

A block of code is set as follows:

df_data_2.createOrReplaceTempView("station")
sqlDF = spark.sql("SELECT * FROM station where VALUE > 200")
sqlDF.show()

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

[default]
exten => s,1,Dial(Zap/1|30)
exten => s,2,Voicemail(u100)
exten => s,102,Voicemail(b100)
exten => i,1,Voicemail(s0)

Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "If you click on the blue Cloud sign-up/log-in link, you can create a free account (using your IBM ID) or log in (once you have set up your paid or free account)."

Warnings or important notes appear like this.
Tips and tricks appear like this.

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