Hands-On Machine Learning with IBM Watson: Leverage IBM Watson to implement machine learning techniques and algorithms using Python


Hands-On Machine Learning with IBM Watson: Leverage IBM Watson to implement machine learning techniques and algorithms using Python
By 作者: James D. Miller
ISBN-10 书号: 1789611857
ISBN-13 书号: 9781789611854
Release Finelybook 出版日期: 2019-03-29
pages 页数: (288 )

The Book Description

More Information
Learn
Understand key characteristics of IBM machine learning services
Run supervised and unsupervised techniques in the cloud
Understand how to create a Spark pipeline in Watson Studio
Implement deep learning and neural networks on the IBM Cloud with TensorFlow
Create a complete, cloud-based facial expression classification solution
Use biometric traits to build a cloud-based human identification system
About
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.

Features
Implement data science and machine learning techniques to draw insights from real-world data
Understand what IBM Cloud platform can help you to implement cognitive insights within applications
Understand the role of data representation and feature extraction in any machine learning system

contents
1 Introduction to IBM Cloud
2 Feature Extraction - A Bag of Tricks
3 Supervised Machine Learning Models for Your Data
4 Implementing Unsupervised Algorithms
5 Machine Learning Workouts on IBM Cloud
6 Using Spark with IBM Watson Studio
7 Deep Learning Using TensorFlow on the IBM Cloud
8 Creating a Facial Expression Platform on IBM Cloud
9 The Automated Classification of Lithofacies Formation Using ML
10 Building a Cloud-Based Multibiometric Identity Authentication Platform

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