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CompTIA DataX Study Guide: Exam DY0-001 (Sybex Study Guide) 1st Edition 2024 with complete solution $20.49   Add to cart

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CompTIA DataX Study Guide: Exam DY0-001 (Sybex Study Guide) 1st Edition 2024 with complete solution

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  • CompTIA DataX
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  • CompTIA DataX

CompTIA DataX Study Guide: Exam DY0-001 (Sybex Study Guide) 1st Edition 2024 with complete solution In CompTIA DataX Study Guide: Exam DY0-001, data scientist and analytics professor, Fred Nwanganga, delivers a practical, hands-on guide to establishing your credentials as a data science practiti...

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  • August 9, 2024
  • 590
  • 2024/2025
  • Exam (elaborations)
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  • CompTIA DataX
  • CompTIA DataX
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Wiseman
,Table of Contents
Cover
Table of Contents
Title Page
Copyright
Dedication
Acknowledgments
About the Author
About the Technical Editor
Introduction
About the DataX Certification
How This Book Is Organized
Interactive Online Learning Environment and Test Bank
How to Contact the Publisher
Assessment Test
Answers to Assessment Test
Chapter 1: What Is Data Science?
Data Science
Data Science Best Practices
Summary
Exam Essentials
Review Questions
Chapter 2: Mathematics and Statistical Methods
Calculus
Probability Distributions
Inferential Statistics
Linear Algebra

, Summary
Exam Essentials
Review Questions
Chapter 3: Data Collection and Storage
Common Data Sources
Data Ingestion
Data Storage
Managing the Data Lifecycle
Summary
Exam Essentials
Review Questions
Chapter 4: Data Exploration and Analysis
Exploratory Data Analysis
Common Data Quality Issues
Summary
Exam Essentials
Review Questions
Chapter 5: Data Processing and Preparation
Data Transformation
Data Enrichment and Augmentation
Data Cleaning
Handling Class Imbalance
Summary
Exam Essentials
Review Questions
Chapter 6: Modeling and Evaluation
Types of Models
Model Design Concepts
Model Evaluation

, Summary
Exam Essentials
Review Questions
Chapter 7: Model Validation and Deployment
Model Validation
Communicating Results
Model Deployment
Machine Learning Operations (MLOps)
Summary
Exam Essentials
Review Questions
Chapter 8: Unsupervised Machine Learning
Association Rules
Clustering
Dimensionality Reduction
Recommender Systems
Summary
Exam Essentials
Review Questions
Chapter 9: Supervised Machine Learning
Linear Regression
Logistic Regression
Discriminant Analysis
Naive Bayes
Decision Trees
Ensemble Methods
Summary
Exam Essentials
Review Questions

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