Price: $27.00
(as of Dec 18,2024 06:53:09 UTC – Details)
ASIN : B0BW2X919P
Publisher : Independently published (February 27, 2023)
Language : English
Paperback : 104 pages
ISBN-13 : 979-8377509356
Item Weight : 9.4 ounces
Dimensions : 7.44 x 0.24 x 9.69 inches
Introduction To Conformal Prediction With Python: A Short Guide For Quantifying Uncertainty Of Machine Learning Models
Conformal prediction is a powerful framework for quantifying uncertainty in machine learning models. By providing prediction intervals that come with a guarantee of coverage, conformal prediction allows us to assess the reliability of our model’s predictions.
In this short guide, we will introduce you to the basics of conformal prediction and show you how to implement it in Python. We will cover the following topics:
- What is conformal prediction and why is it important?
- How does conformal prediction work?
- Implementing conformal prediction in Python using the
cprlibrary - Evaluating the uncertainty of machine learning models using conformal prediction
By the end of this guide, you will have a solid understanding of how conformal prediction can help you quantify the uncertainty of your machine learning models and make more informed decisions based on their predictions. Let’s get started!
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