March 2019
Beginner to intermediate
288 pages
6h 21m
English
Overview
Hands-On Machine Learning with IBM Watson is an essential guide for mastering machine learning techniques and implementing them on the IBM Cloud platform using Python. With this book, you'll delve into a range of machine learning concepts, learn about supervised and unsupervised learning techniques, explore deep learning principles, and gain hands-on experience with practical, real-world applications.
What this Book will help me do
- Gain expertise in leveraging IBM machine learning services and the IBM Cloud to develop modern machine learning solutions.
- Understand how to utilize supervised and unsupervised learning methods for robust data analysis.
- Learn to create and optimize Spark pipelines in Watson Studio for efficient data handling workflows.
- Get hands-on with deep learning and neural network implementations using TensorFlow on the IBM platform.
- Build practical cloud-based projects such as a facial recognition system and a multi-biometric authentication platform.
Author(s)
James D. Miller is a seasoned data scientist and machine learning enthusiast with years of experience using IBM Cloud for building intelligent applications. With a strong background in applied data science, James has taught and guided numerous professionals in mastering machine learning. His practical and approachable writing style ensures readers gain clear and actionable insights.
Who is it for?
This book is designed for data scientists and machine learning engineers who want to explore IBM Cloud and its capabilities in solving real-world problems. Whether you're new to the platform or eager to develop practical expertise in leveraging IBM Watson for machine learning projects, this book is an excellent fit if you have basic Python and machine learning knowledge and seek hands-on technical growth.
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