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Machine learning concepts with Pytho...

Silaparasetty, Nikita.

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Machine learning concepts with Python and the Jupyter Notebook environment = using Tensorflow 2.0 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning concepts with Python and the Jupyter Notebook environment/ by Nikita Silaparasetty.
Reminder of title:	using Tensorflow 2.0 /
Author:	Silaparasetty, Nikita.
Published:	Berkeley, CA :Apress : : 2020.,
Description:	xxvii, 290 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1: An Overview of Artificial Intelligence -- Chapter 2: An Overview of Machine Learning -- Chapter 3: Introduction to Deep Learning -- Chapter 4: Machine Learning Versus Deep Learning -- Chapter 5: Machine Learning with Python -- Chapter 6: Introduction to Jupyter Notebooks -- Chapter 7: Python Programming on the Jupyter Notebook -- Chapter 8: The Tensorflow Machine Learning Library -- Chapter 9: Programming with Tensorflow 1.0 -- Chapter 10: Introducing TensorFlow 2.0 -- Chapter 11: Machine Learning Programming with TensorFlow 2.0.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-1-4842-5967-2
ISBN:	9781484259672

Machine learning concepts with Python and the Jupyter Notebook environment = using Tensorflow 2.0 /
Silaparasetty, Nikita.

Machine learning concepts with Python and the Jupyter Notebook environmentusing Tensorflow 2.0 /[electronic resource] :by Nikita Silaparasetty. - Berkeley, CA :Apress :2020. - xxvii, 290 p. :ill., digital ;24 cm.

Chapter 1: An Overview of Artificial Intelligence -- Chapter 2: An Overview of Machine Learning -- Chapter 3: Introduction to Deep Learning -- Chapter 4: Machine Learning Versus Deep Learning -- Chapter 5: Machine Learning with Python -- Chapter 6: Introduction to Jupyter Notebooks -- Chapter 7: Python Programming on the Jupyter Notebook -- Chapter 8: The Tensorflow Machine Learning Library -- Chapter 9: Programming with Tensorflow 1.0 -- Chapter 10: Introducing TensorFlow 2.0 -- Chapter 11: Machine Learning Programming with TensorFlow 2.0.

Create, execute, modify, and share machine learning applications with Python in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebooks instead of a text editor or a regular IDE. You'll start by learning fundamental concepts in Python necessary for working with machine learning application development. Then use Jupyter Notebooks to improve the way you program with Python. After grounding your skills in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book. Those who are new to machine learning can start in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier. You will: Program machine learning models in Python Tackle basic machine learning obstacles Develop in the Jupyter Notebooks environment.

ISBN: 9781484259672

Standard No.: 10.1007/978-1-4842-5967-2doiSubjects--Uniform Titles:

TensorFlow.
Subjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .S55 2020

Dewey Class. No.: 006.31

Machine learning concepts with Python and the Jupyter Notebook environment = using Tensorflow 2.0 /
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245 1 0 $a Machine learning concepts with Python and the Jupyter Notebook environment $h [electronic resource] : $b using Tensorflow 2.0 / $c by Nikita Silaparasetty.
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505 0 $a Chapter 1: An Overview of Artificial Intelligence -- Chapter 2: An Overview of Machine Learning -- Chapter 3: Introduction to Deep Learning -- Chapter 4: Machine Learning Versus Deep Learning -- Chapter 5: Machine Learning with Python -- Chapter 6: Introduction to Jupyter Notebooks -- Chapter 7: Python Programming on the Jupyter Notebook -- Chapter 8: The Tensorflow Machine Learning Library -- Chapter 9: Programming with Tensorflow 1.0 -- Chapter 10: Introducing TensorFlow 2.0 -- Chapter 11: Machine Learning Programming with TensorFlow 2.0.
520 $a Create, execute, modify, and share machine learning applications with Python in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebooks instead of a text editor or a regular IDE. You'll start by learning fundamental concepts in Python necessary for working with machine learning application development. Then use Jupyter Notebooks to improve the way you program with Python. After grounding your skills in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book. Those who are new to machine learning can start in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier. You will: Program machine learning models in Python Tackle basic machine learning obstacles Develop in the Jupyter Notebooks environment.
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