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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

Classification

Being able to put things into certain classes might be the most common type of ML application that you see in the world, and has been a staple of the industry for a long time.

There are two main types of classification: binary classification and multi-class classification. As the names indicate, binary classification is when the outcome only has two possible options. It's very common to have a true or false outcome in this setup.

Multi-class classification is when there are more than two possible classes. This could be for a variety of scenarios, such as movie genre. The approaches taken for them are very similar to a binary classification problem.

Let's check out some examples that might help you get a better grasp on problems that fall into the classification bucket:

Whether emails are spam or not (binary)

  • Whether you would survive the Titanic sinking (binary)
  • Identifying the type of flower (multi-class)
  • Labeling handwritten...
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