國立高雄大學圖資館 |

Language: English

Back

Machine learning concepts with Pytho...

Silaparasetty, Nikita.

Machine learning concepts with Python and the Jupyter Notebook environmentusing Tensorflow 2.0 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning concepts with Python and the Jupyter Notebook environmentby 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.
Contained By:	Springer Nature eBook
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-1-4842-5967-2
ISBN:	9781484259672$q(electronic bk.)

Machine learning concepts with Python and the Jupyter Notebook environmentusing 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$q(electronic bk.)

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

TensorFlow.
Subjects--Topical Terms:

188639
Machine learning.

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

Dewey Class. No.: 006.31

Machine learning concepts with Python and the Jupyter Notebook environmentusing Tensorflow 2.0 /
LDR:02753nmm a2200325 a 4500 001 586383
003 DE-He213
005 20210201103333.0
006 m d
007 cr nn 008maaau
008 210323s2020 cau s 0 eng d
020 $a 9781484259672$q(electronic bk.)
020 $a 9781484259665$q(paper)
024 7 $a 10.1007/978-1-4842-5967-2 $2 doi
035 $a 978-1-4842-5967-2
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .S55 2020
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .S581 2020
100 1 $a Silaparasetty, Nikita. $3 877802
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.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2020.
300 $a xxvii, 290 p. : $b ill., digital ; $c 24 cm.
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.
630 0 0 $a TensorFlow. $3 864055
650 0 $a Machine learning. $3 188639
650 0 $a Python (Computer program language) $3 215247
650 0 $a Information visualization. $3 248886
650 1 4 $a Artificial Intelligence. $3 212515
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-5967-2
950 $a Professional and Applied Computing (SpringerNature-12059)