机读格式显示(MARC)

• 000 03043cam a2200373 i 4500

• 001 0000969689

• 003 CAL

• 005 20231102161600.0

• 008 220916s2022 njua b 000 0 eng d

• 020 __ |a 9781119857334 |q (hbk.)

• 020 __ |z 9781119857990 |q (ePub ebook)

• 040 __ |a UKMGB |b eng |e rda |c UKMGB |d BDX |d OCLCF

• 082 04 |a 005.7 |2 23

• 090 __ |a TP274/P898

• 093 __ |a TP274 |2 5

• 099 __ |a CAL 022023051550

• 100 1_ |a Prakash, Kolla Bhanu, |e author.

• 245 10 |a Data science handbook : |b a practical approach / |c Kolla Bhanu Prakash.

• 260 __ |a Hoboken : |b Wiley ; |a Beverly, MA. : |b Scrivener, |c 2022.

• 300 __ |a xiii, 453 pages : |b illustrations ; |c 24 cm.

• 336 __ |a text |2 rdacontent

• 337 __ |a unmediated |2 rdamedia

• 338 __ |a volume |2 rdacarrier

• 490 0_ |a Next-generation computing and communication engineering

• 504 __ |a Includes bibliographical references.

• 505 0_ |a Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgment -- Preface -- 1 Data Munging Basics -- 1 Introduction -- 1.1 Filtering and Selecting Data -- 1.2 Treating Missing Values -- 1.3 Removing Duplicatesduplicates -- 1.4 Concatenating and Transforming Data -- 1.5 Grouping and Data Aggregation -- References -- 2 Data Visualization -- 2.1 Creating Standard Plots (Line, Bar, Pie) -- 2.2 Defining Elements of a Plot -- 2.3 Plot Formatting Segment 3 Plot formatting -- 2.4 Creating Labels and Annotations -- 2.5 Creating Visualizations from Time Series Data -- 2.6 Constructing Histograms, Box Plots, and Scatter Plots -- References -- 3 Basic Math and Statistics -- 3.1 Linear Algebra -- 3.2 Calculus -- 3.2.1 Differential Calculus -- 3.2.2 Integral Calculus -- Statistics for Data Science -- 3.3 Inferential Statistics -- 3.3.1 Central Limit Theorem -- 3.3.2 Hypothesis Testing -- 3.3.3 ANOVA -- 3.3.4 Qualitative Data Analysis -- 3.4 Using NumPy to Perform Arithmetic Operations on Data -- 3.5 Generating Summary Statistics Using Pandas and Scipy -- 3.6 Summarizing Categorical Data Using Pandas -- 3.7 Starting with Parametric Methods in Pandas and Scipy -- 3.8 Delving Into Non-Parametric Methods Using Pandas and Scipy -- 3.9 Transforming Dataset Distributions -- References -- 4 Introduction to Machine Learning -- 4.1 Introduction to Machine Learning -- 4.2 Types of Machine Learning Algorithms -- 4.3 Explanatory Factor Analysis -- 4.4 Principal Component Analysis (PCA) -- References -- 5 Outlier Analysis -- 5.1 Extreme Value Analysis Using Univariate Methods -- 5.2 Multivariate Analysis for Outlier Detection -- 5.3 DBSCan Clustering to Identify Outliers -- References -- 6 Cluster Analysis -- 6.1 K-Means Algorithm -- 6.2 Hierarchial Methods -- 6.3 Instance-Based Learning w/k-Nearest Neighbor.

• 650 _0 |a Big data.

• 650 _0 |a Data mining.

• 650 _0 |a Quantitative research.

• 650 _0 |a Information visualization.

• 700 1_ |a Prakash, Kolla Bhanu, |e editor.

• 776 08 |i ebook version : |z 9781119857990

• 920 __ |a 242450 |z 1

• 998 __ |a WUL