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TensorFlow: Powerful Predictive Analytics with TensorFlow

You're reading from  TensorFlow: Powerful Predictive Analytics with TensorFlow

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781789136913
Pages 164 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Md. Rezaul Karim Md. Rezaul Karim
Profile icon Md. Rezaul Karim
LinkedIn
Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.
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Table of Contents (8) Chapters

TensorFlow: Powerful Predictive Analytics with TensorFlow
Credits
Preface
1. From Data to Decisions – Getting Started with TensorFlow 2. Putting Data in Place – Supervised Learning for Predictive Analytics 3. Clustering Your Data – Unsupervised Learning for Predictive Analytics 4. Using Reinforcement Learning for Predictive Analytics Assessment Answers

Lesson 3: Clustering Your Data – Unsupervised Learning for Predictive Analytics

Question Number

Answer

1

Supervised

2

True

3

The main objective of the unsupervised learning algorithms is to explore the unknown/hidden patterns in the input data that are unlabeled

4

True

5

3

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Authors (1)

Profile icon Md. Rezaul Karim
LinkedIn
Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.
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