語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Learn data mining through Excel = a step-by-step approach for understanding machine learning methods /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Learn data mining through Excel/ by Hong Zhou.
其他題名:
a step-by-step approach for understanding machine learning methods /
作者:
Zhou, Hong.
出版者:
Berkeley, CA :Apress : : 2023.,
面頁冊數:
xi, 288 p. :ill., digital ; : 24 cm.;
Contained By:
Springer Nature eBook
標題:
Data Mining and Knowledge Discovery. -
電子資源:
https://doi.org/10.1007/978-1-4842-9771-1
ISBN:
9781484297711
Learn data mining through Excel = a step-by-step approach for understanding machine learning methods /
Zhou, Hong.
Learn data mining through Excel
a step-by-step approach for understanding machine learning methods /[electronic resource] :by Hong Zhou. - Second edition. - Berkeley, CA :Apress :2023. - xi, 288 p. :ill., digital ;24 cm.
Chapter 1: Excel and Data Mining -- Chapter 2: Linear Regression -- Chapter 3: K-Means Clustering -- Chapter 4: Linear Discriminant Analysis -- Chapter 5: Cross Validation and ROC -- Chapter 6: Logistic Regression -- Chapter 7: K-nearest Neighbors -- Chapter 8: Naïve Bayes Classification -- Chapter 9: Decision Trees -- Chapter 10: Association Analysis -- Chapter 11: Artificial Neural Networks -- Chapter 12: Text Mining -- Chapter 13: Hierarchical Clustering and Dendrogram -- Chapter 14 Exploratory Data Analysis (EDA) -- Chapter 15: After Excel.
Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Most software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help, and this book will show you exactly how. This updated edition demonstrates how to work with data in a transparent manner using Excel. When you open an Excel file, data is visible immediately and you can work with it directly. You'll see how to examine intermediate results even as you are still conducting your mining task, offering a deeper understanding of how data is manipulated, and results are obtained. These are critical aspects of the model construction process that are often hidden in software tools and programming language packages. Over the course of Learn Data Mining Through Excel, you will learn the data mining advantages the application offers when the data sets are not too large. You'll see how to use Excel's built-in features to create visual representations of your data, enabling you to present your findings in an accessible format. Author Hong Zhou walks you through each step, offering not only an active learning experience, but teaching you how the mining process works and how to find hidden patterns within the data. Upon completing this book, you will have a thorough understanding of how to use an application you very likely already have to mine and analyze data, and how to present results in various formats. You will: Comprehend data mining using a visual step-by-step approach Gain an introduction to the fundamentals of data mining Implement data mining methods in Excel Understand machine learning algorithms Leverage Excel formulas and functions creatively Obtain hands-on experience with data mining and Excel.
ISBN: 9781484297711
Standard No.: 10.1007/978-1-4842-9771-1doiSubjects--Uniform Titles:
Microsoft Excel (Computer file)
Subjects--Topical Terms:
677765
Data Mining and Knowledge Discovery.
LC Class. No.: QA76.9.D343 / Z46 2023
Dewey Class. No.: 006.312
Learn data mining through Excel = a step-by-step approach for understanding machine learning methods /
LDR
:03516nam a2200337 a 4500
001
1117198
003
DE-He213
005
20230929224630.0
006
m d
007
cr nn 008maaau
008
240124s2023 cau s 0 eng d
020
$a
9781484297711
$q
(electronic bk.)
020
$a
9781484297704
$q
(paper)
024
7
$a
10.1007/978-1-4842-9771-1
$2
doi
035
$a
978-1-4842-9771-1
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.D343
$b
Z46 2023
072
7
$a
UMP
$2
bicssc
072
7
$a
COM051380
$2
bisacsh
072
7
$a
UMP
$2
thema
082
0 4
$a
006.312
$2
23
090
$a
QA76.9.D343
$b
Z63 2023
100
1
$a
Zhou, Hong.
$3
1063167
245
1 0
$a
Learn data mining through Excel
$h
[electronic resource] :
$b
a step-by-step approach for understanding machine learning methods /
$c
by Hong Zhou.
250
$a
Second edition.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2023.
300
$a
xi, 288 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Chapter 1: Excel and Data Mining -- Chapter 2: Linear Regression -- Chapter 3: K-Means Clustering -- Chapter 4: Linear Discriminant Analysis -- Chapter 5: Cross Validation and ROC -- Chapter 6: Logistic Regression -- Chapter 7: K-nearest Neighbors -- Chapter 8: Naïve Bayes Classification -- Chapter 9: Decision Trees -- Chapter 10: Association Analysis -- Chapter 11: Artificial Neural Networks -- Chapter 12: Text Mining -- Chapter 13: Hierarchical Clustering and Dendrogram -- Chapter 14 Exploratory Data Analysis (EDA) -- Chapter 15: After Excel.
520
$a
Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Most software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help, and this book will show you exactly how. This updated edition demonstrates how to work with data in a transparent manner using Excel. When you open an Excel file, data is visible immediately and you can work with it directly. You'll see how to examine intermediate results even as you are still conducting your mining task, offering a deeper understanding of how data is manipulated, and results are obtained. These are critical aspects of the model construction process that are often hidden in software tools and programming language packages. Over the course of Learn Data Mining Through Excel, you will learn the data mining advantages the application offers when the data sets are not too large. You'll see how to use Excel's built-in features to create visual representations of your data, enabling you to present your findings in an accessible format. Author Hong Zhou walks you through each step, offering not only an active learning experience, but teaching you how the mining process works and how to find hidden patterns within the data. Upon completing this book, you will have a thorough understanding of how to use an application you very likely already have to mine and analyze data, and how to present results in various formats. You will: Comprehend data mining using a visual step-by-step approach Gain an introduction to the fundamentals of data mining Implement data mining methods in Excel Understand machine learning algorithms Leverage Excel formulas and functions creatively Obtain hands-on experience with data mining and Excel.
630
0 0
$a
Microsoft Excel (Computer file)
$3
558412
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
677765
650
1 4
$a
Microsoft.
$3
1387749
650
0
$a
Data mining.
$3
528622
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
856
4 0
$u
https://doi.org/10.1007/978-1-4842-9771-1
950
$a
Professional and Applied Computing (SpringerNature-12059)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入