Part 2: Preparing Your Learning Tools
by Luca Massaron, John Paul Mueller
Machine Learning For Dummies
- Cover
- Cover
- Introduction
- Part 1: Introducing How Machines Learn
- Part 2: Preparing Your Learning Tools
- Part 3: Getting Started with the Math Basics
- Chapter 9: Demystifying the Math Behind Machine Learning
- Chapter 10: Descending the Right Curve
- Chapter 11: Validating Machine Learning
- Checking Out-of-Sample Errors
- Getting to Know the Limits of Bias
- Keeping Model Complexity in Mind
- Keeping Solutions Balanced
- Training, Validating, and Testing
- Resorting to Cross-Validation
- Looking for Alternatives in Validation
- Optimizing Cross-Validation Choices
- Avoiding Sample Bias and Leakage Traps
- Chapter 12: Starting with Simple Learners
- Part 4: Learning from Smart and Big Data
- Part 5: Applying Learning to Real Problems
- Part 6: The Part of Tens
- About the Author
- Advertisement Page
- Connect with Dummies
- End User License Agreement
Part 2
Preparing Your Learning Tools
IN THIS PART …
Creating an R setup
Performing basic R tasks
Creating a Python setup
Performing basic Python tasks
Working with other machine learning tools
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