book

CompTIA DataX Study Guide

by Fred Nwanganga

August 2024

Beginner to intermediate

416 pages

11h 28m

English

Sybex

Read now

Unlock full access

About the DataX CertificationHow This Book Is OrganizedInteractive Online Learning Environment and Test BankHow to Contact the PublisherAssessment TestAnswers to Assessment Test
Data ScienceData Science Best PracticesSummaryExam EssentialsReview Questions

CalculusProbability DistributionsInferential StatisticsLinear AlgebraSummaryExam EssentialsReview Questions
Common Data SourcesData IngestionData StorageManaging the Data LifecycleSummaryExam EssentialsReview Questions
Exploratory Data AnalysisCommon Data Quality IssuesSummaryExam EssentialsReview Questions
Data TransformationData Enrichment and AugmentationData CleaningHandling Class ImbalanceSummaryExam EssentialsReview Questions
Types of ModelsModel Design ConceptsModel EvaluationSummaryExam EssentialsReview Questions
Model ValidationCommunicating ResultsModel DeploymentMachine Learning Operations (MLOps)SummaryExam EssentialsReview Questions
Association RulesClusteringDimensionality ReductionRecommender SystemsSummaryExam EssentialsReview Questions
Linear RegressionLogistic RegressionDiscriminant AnalysisNaive BayesDecision TreesEnsemble MethodsSummaryExam EssentialsReview Questions
Artificial Neural NetworksDeep Neural NetworksSummaryExam EssentialsReview Questions
Natural Language ProcessingText PreparationText RepresentationSummaryExam EssentialsReview Questions
OptimizationComputer VisionSummaryExam EssentialsReview Questions
Chapter 1: What Is Data Science?Chapter 2: Mathematics and Statistical MethodsChapter 3: Data Collection and StorageChapter 4: Data Exploration and AnalysisChapter 5: Data Processing and PreparationChapter 6: Modeling and EvaluationChapter 7: Model Validation and DeploymentChapter 8: Unsupervised Machine LearningChapter 9: Supervised Machine LearningChapter 10: Neural Networks and Deep LearningChapter 11: Natural Language ProcessingChapter 12: Specialized Applications of Data Science

Content preview from CompTIA DataX Study Guide

Chapter 12Specialized Applications of Data Science

THE COMPTIA DATAX EXAM OBJECTIVES COVERED IN THIS CHAPTER INCLUDE:

Domain 5: Specialized Applications of Data Science
- 5.1 Compare and contrast optimization concepts.
- 5.3 Explain the use and importance of computer vision concepts.

Data science encompasses a broad spectrum of applications across various domains. In this chapter, we delve into the application of data science within the specialized areas of optimization and computer vision. We start by exploring the fundamentals of numerical optimization, covering key components such as decision variables, the objective function, and constraints. We then examine both constrained and unconstrained optimization problems. Following this, ...