國立高雄大學圖資館 |

Language: English

Back

Mastering machine learning with Pyth...

SpringerLink (Online service)

Mastering machine learning with Python in six stepsa practical Implementation guide to predictive data analytics using Python /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mastering machine learning with Python in six stepsby Manohar Swamynathan.
Reminder of title:	a practical Implementation guide to predictive data analytics using Python /
Author:	Swamynathan, Manohar.
Published:	Berkeley, CA :Apress :2017.
Description:	xxi, 358 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Python (Computer program language)
Online resource:	http://dx.doi.org/10.1007/978-1-4842-2866-1
ISBN:	9781484228661$q(electronic bk.)

Mastering machine learning with Python in six stepsa practical Implementation guide to predictive data analytics using Python /
Swamynathan, Manohar.

Mastering machine learning with Python in six stepsa practical Implementation guide to predictive data analytics using Python /[electronic resource] :by Manohar Swamynathan. - Berkeley, CA :Apress :2017. - xxi, 358 p. :ill., digital ;24 cm.

Chapter 1: Getting Started in Python -- Chapter 2: Introduction to Machine Learning -- Chapter 3: Fundamentals of Machine Learning -- Chapter 4: Model Diagnosis and Tuning -- Chapter 5: Text Mining -- Chapter 6: Demystifying Neural Network -- Chapter 7: Conclusion.

Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You'll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you'll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage.

ISBN: 9781484228661$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-2866-1doiSubjects--Topical Terms:

215247
Python (Computer program language)

LC Class. No.: QA76.73.P98

Dewey Class. No.: 005.133

Mastering machine learning with Python in six stepsa practical Implementation guide to predictive data analytics using Python /
LDR:02399nmm a2200325 a 4500 001 518033
003 DE-He213
005 20180110104936.0
006 m d
007 cr nn 008maaau
008 180316s2017 cau s 0 eng d
020 $a 9781484228661$q(electronic bk.)
020 $a 9781484228654$q(paper)
024 7 $a 10.1007/978-1-4842-2866-1 $2 doi
035 $a 978-1-4842-2866-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.73.P98
072 7 $a UMA $2 bicssc
072 7 $a COM014000 $2 bisacsh
072 7 $a COM018000 $2 bisacsh
082 0 4 $a 005.133 $2 23
090 $a QA76.73.P98 $b S971 2017
100 1 $a Swamynathan, Manohar. $3 787978
245 1 0 $a Mastering machine learning with Python in six steps $h [electronic resource] : $b a practical Implementation guide to predictive data analytics using Python / $c by Manohar Swamynathan.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2017.
300 $a xxi, 358 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Getting Started in Python -- Chapter 2: Introduction to Machine Learning -- Chapter 3: Fundamentals of Machine Learning -- Chapter 4: Model Diagnosis and Tuning -- Chapter 5: Text Mining -- Chapter 6: Demystifying Neural Network -- Chapter 7: Conclusion.
520 $a Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You'll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you'll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage.
650 0 $a Python (Computer program language) $3 215247
650 0 $a Data mining. $3 184440
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Computing Methodologies. $3 274528
650 2 4 $a Big Data. $3 760530
650 2 4 $a Open Source. $3 758930
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-1-4842-2866-1
950 $a Professional and Applied Computing (Springer-12059)