PRAKTISCHES MASCHINELLES LERNEN MIT IBM WATSON: HEBEL IBM von D. James Miller *NEU*-

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HANDS-ON MACHINE LEARNING WITH IBM WATSON: LEVERAGE IBM By D. James Miller *NEW*
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ISBN-10
1789611857
Book Title
Hands-On Machine Learning with IBM Watson: Leverage IBM Watson to
Item Height
9.25 inches
ISBN
9781789611854
Kategorie

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Product Identifiers

Publisher
Packt Publishing, The Limited
ISBN-10
1789611857
ISBN-13
9781789611854
eBay Product ID (ePID)
27038489640

Product Key Features

Number of Pages
288 Pages
Language
English
Publication Name
Hands-On Machine Learning with IBM Watson : Leverage IBM Watson to Implement Machine Learning Techniques and Algorithms Using Python
Publication Year
2019
Subject
Enterprise Applications / Collaboration Software, Computer Vision & Pattern Recognition, Programming Languages / Python, Information Technology
Type
Textbook
Author
James D. Miller
Subject Area
Computers
Format
Trade Paperback

Dimensions

Item Length
3.6 in
Item Width
3 in

Additional Product Features

Intended Audience
Trade
Table Of Content
Table of Contents Introduction to IBM Cloud Feature Extraction - A Bag of Tricks Supervised Machine Learning Models for Your Data Implementing Unsupervised Algorithms Machine Learning Workouts on IBM Cloud Using SPARK with IBM Watson Studio Deep Learning Using TensorFlow on the IBM Cloud Creating a Facial Expression Platform on the IBM Cloud Automated Classification of Lithofacies Formation Using Machine Learning Building a Cloud-Based Multi-Biometric Identity Authentication Platform
Synopsis
A practical guide on Machine learning with IBM cloud to act as a solid yet concise reference for the readers. You will learn about the role of data representation and feature extraction in machine learning. This book will help you learn how to use the IBM Cloud and Watson Machine learning service to develop real-world machine learning solutions., Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key 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 Book Description 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. What you will 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 Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.

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