Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

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IndexSingle linkage method, 90Sparkadvantage, 166broadcast variable, 167components, 166lineage, 167message-passinginterface, 167partition, 167RDD, 167shared variable, 167Spark Core, 168word count program, 167Squared Euclidean distance, 84Stationary time seriesautocorrelation andcorrelogram, 129, 130autocovariance, 129description, 128joint distribution, 128Supervised learningclassifications, 57dealing, categoricaldata, 73–76decision tree, 59–61dimensionality reductioninvestment banking, 50mutual information (MI), 56Pearson correlation, 50–52principal componentanalysis, 53–55survey/factor analysis, 49weighted average ofinstruments, 50image recognition, 67Naive Bayes classifier, 61–62nearest neighborclassifier, 64over-or under-predictintentionally, 71–72regression (see Regression)semi, 58sentiment analysis, 65–66support vectormachine, 62–63Support vector machine, 62–63TTopical crawling, 40TensorFlowlogistic regresson, 111–112multilayer linear regression,108–109, 111simple linear regression,106, 108Time seriesARMA models, 137–139AR model, 133definition, 121exceptional scenario, 141, 143Fourier Transform, 140MA model, 131–133missing data, 143SciPy, 130seasonality, 124–126stationary (see Stationary timeseries)185
IndexTime series (cont.)transformationcyclic variation, 127data distributionnormal, 127irregular fluctuations, 128seasonal effect additive, 127variance stabilization, 126trends, 121–122curve fitting, 122removing, 123–124variation, 121Topical crawling, 42–48U, V, W, X, Y, ZUnsupervised learning, seeClustering186
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AdvancedData AnalyticsUsing PythonW
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Advanced Data Analytics Using Pytho
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Table of ContentsAbout the Authorxi
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Table of ContentsNaive Bayes Classi
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Table of ContentsTime-Series Analys
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About the Technical ReviewerSundar
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CHAPTER 1IntroductionIn this book,
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Chapter 1IntroductionOOP in PythonB
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Chapter 1Introductionif pageFile.ge
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Chapter 1Introductiondef parseSoupT
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Chapter 1Introductionsuper(AirLineR
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Chapter 1Introductionif "Value" in
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Chapter 1Introductionavailable in R
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Chapter 1Introductiong.scores = Tab
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Chapter 1Introductionif f == 'clien
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Chapter 1Introductionmetadata1 = Me
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Chapter 1Introduction(pred4,prob4)
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CHAPTER 2ETL with Python(Structured
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Chapter 2ETL with Python (Structure
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CHAPTER 3Supervised LearningUsing P
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Chapter 3Supervised Learning Using
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Decision TreeChapter 3 Supervised L
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CHAPTER 4UnsupervisedLearning: Clus
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Chapter 4Unsupervised Learning: Clu
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General and Euclidean DistanceThe d
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Chapter 4Graph Theoretical Approach
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CHAPTER 5Deep Learningand Neural Ne
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Chapter 5Deep Learning and Neural N
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Chapter 6Time SeriesFigure 6-1. A t
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Chapter 6Time SeriesA trend can be
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Chapter 6Time SeriesThe simple movi
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Chapter 6Time SeriesIrregular Fluct
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Chapter 6Time SeriesFigure 6-2 show
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Page 191 and 192: IndexCollaborative filtering, 52Com
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Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

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