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Building Data Science Solutions with Anaconda

You're reading from  Building Data Science Solutions with Anaconda

Product type Book
Published in May 2022
Publisher Packt
ISBN-13 9781800568785
Pages 330 pages
Edition 1st Edition
Languages
Author (1):
Dan Meador Dan Meador
Profile icon Dan Meador

Table of Contents (16) Chapters

Preface 1. Part 1: The Data Science Landscape – Open Source to the Rescue
2. Chapter 1: Understanding the AI/ML landscape 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

Defining your problem

Many times, you'll see AI books and blogs talking about the distinct types of AI problems falling into the following categories:

  • Supervised
  • Unsupervised
  • Semi-supervised
  • Reinforcement

We did the same thing back in Chapter 1, Understanding the AI/ML Landscape, and you can find a flowchart of how to decide what category your situation falls into in Figure 7.1:

Figure 7.1 – Dataset heuristics for choosing your AI family

This is a good idea, but when you are starting with a problem, you aren't always thinking about it in terms of the problem type but more in terms of what solution you are trying to figure out.

We'll look at a few different and very common problem types in the following sections. They do not encompass every problem family that you will come across, but they will serve many of them.

Model problem types

The following are the four core problem types that we'll focus...

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