Machine Learning Pitfalls - A Brief Guide on How to Avoid Common Pitfalls (With Code Samples)
Machine Learning Pitfalls - A Brief Guide on How to Avoid Common Pitfalls (With Code Samples)
About the Book
This book will be a helpful resource for anyone interested in avoiding the pitfalls of machine learning and building trustworthy models. Whether you are a seasoned machine learning practitioner or a newcomer to the field, the lessons in this book will be valuable to you.
The paperback is available on Amazon: Machine Learning Pitfalls - A Brief Guide on How to Avoid Common Pitfalls (With Code Samples)
About the Author
Table of Contents
- Overview
- Why machine learning is prone to pitfalls
- The importance of avoiding pitfalls
- The importance of high-quality data
- Common issues in data collection and preparation
- Strategies for overcoming data-related pitfalls
- Understanding different types of models
- The importance of choosing the right model
- How to evaluate model performance
- Overfitting and Underfitting
- The dangers of overfitting and underfitting
- How to detect and avoid overfitting and underfitting
- The importance of selecting and engineering the right features
- Common pitfalls in feature selection and engineering
- Strategies for avoiding feature-related pitfalls
- Common pitfalls in bias and fairness include:
- Strategies for avoiding bias and ensuring fairness include:
- Understanding bias and fairness in machine learning
- Common sources of bias and unfairness
- How to detect and mitigate bias and unfairness
- Common techniques for improving interpretability and explainability include:
- Why interpretability and explainability are important
- Common challenges in building interpretable and explainable models
- Strategies for improving interpretability and explainability
- The importance of deploying models carefully
- Common pitfalls in model deployment and monitoring
- Strategies for ensuring model reliability and stability
- The ethical implications of machine learning
- How to address ethical concerns in machine learning
- Best practices for ethical machine learning
- Using LIME to explain the decision of a classification model
- Ensuring the robustness of machine learning models
- Prevent overfitting using regularization techniques
- How to diagnose and address underfitting in Python
- How to address class imbalance in Python
- How to address feature selection bias
- Increasing the explainability of machine learning models
- Mitigating bias in machine learning models
- Fairness checking
- Ensuring the safety of machine learning models
- Design
- Development
- Interpret and Communicate
- Deployment
- Threats to data
- Differential privacy
- Distributed and Federated Learning
- Training over encrypted data.
Other books by this author
The Leanpub 60 Day 100% Happiness Guarantee
Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.
Now, this is technically risky for us, since you'll have the book or course files either way. But we're so confident in our products and services, and in our authors and readers, that we're happy to offer a full money back guarantee for everything we sell.
You can only find out how good something is by trying it, and because of our 100% money back guarantee there's literally no risk to do so!
So, there's no reason not to click the Add to Cart button, is there?
See full terms...
80% Royalties. Earn $16 on a $20 book.
We pay 80% royalties. That's not a typo: you earn $16 on a $20 sale. If we sell 5000 non-refunded copies of your book or course for $20, you'll earn $80,000.
(Yes, some authors have already earned much more than that on Leanpub.)
In fact, authors have earnedover $12 millionwriting, publishing and selling on Leanpub.
Learn more about writing on Leanpub
Free Updates. DRM Free.
If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).
Most Leanpub books are available in PDF (for computers) and EPUB (for phones, tablets and Kindle). The formats that a book includes are shown at the top right corner of this page.
Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.
Learn more about Leanpub's ebook formats and where to read them
