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Building Data Science Solutions with Anaconda

You're reading from   Building Data Science Solutions with Anaconda A comprehensive starter guide to building robust and complete models

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Product type Paperback
Published in May 2022
Publisher Packt
ISBN-13 9781800568785
Length 330 pages
Edition 1st Edition
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Author (1):
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Dan Meador Dan Meador
Author Profile Icon Dan Meador
Dan Meador
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Table of Contents (16) Chapters Close

Preface 1. Part 1: The Data Science Landscape – Open Source to the Rescue
2. Chapter 1: Understanding the AI/ML landscape FREE CHAPTER 3. Chapter 2: Analyzing Open Source Software 4. Chapter 3: Using the Anaconda Distribution to Manage Packages 5. Chapter 4: Working with Jupyter Notebooks and NumPy 6. Part 2: Data Is the New Oil, Models Are the New Refineries
7. Chapter 5: Cleaning and Visualizing Data 8. Chapter 6: Overcoming Bias in AI/ML 9. Chapter 7: Choosing the Best AI Algorithm 10. Chapter 8: Dealing with Common Data Problems 11. Part 3: Practical Examples and Applications
12. Chapter 9: Building a Regression Model with scikit-learn 13. Chapter 10: Explainable AI - Using LIME and SHAP 14. Chapter 11: Tuning Hyperparameters and Versioning Your Model 15. Other Books You May Enjoy

Chapter 7: Choosing the Best AI Algorithm

If the field of artificial intelligence and machine learning (commonly referred to as AI/ML) is a car, then the model is the engine. While there are other parts that are critical for its operation, no other aspect gets as much focus and attention. This is for good reason. In the end, the model is the core object that determines whether your outcome is accurate or not, and is the most important artifact from that entire data science workflow.

Which modeling approach is best? That's easy, it depends. For the same reason all cars don't have the same engine, there are many different aspects that go into the best approach to use.

Ask yourself, What problem am I trying to solve? In this chapter, we are going to start with that question, and from there lead you to the modeling approach that would best suit your situation. We'll take a look at the problem type with an example for each algorithm, and look at some of the most widely...

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