Top 10 Best Interpretable Machine Learning

of November 2024
1
Best ChoiceBest Choice
Interpretable Machine Learning with Python: Learn to build interpretable
10
Exceptional
View on Amazon
2
Best ValueBest Value
Explainable AI with Python
9.9
Exceptional
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3
Machine Learning Design Patterns: Solutions to Common Challenges in Data
O'Reilly Media
O'Reilly Media
9.8
Exceptional
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4
Hands-On Explainable AI (XAI) with Python: Interpret, visualize, explain, and
Packt Publishing
Packt Publishing
9.7
Exceptional
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5
Random Forests with R (Use R!)
9.6
Exceptional
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6
Graph Machine Learning: Take graph data to the next level by applying machine
9.5
Excellent
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7
Practical Threat Intelligence and Data-Driven Threat Hunting: A hands-on guide
Packt Publishing
Packt Publishing
9.4
Excellent
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8
Feature Engineering and Selection: A Practical Approach for Predictive Models
Chapman and Hall/CRC
Chapman and Hall/CRC
9.3
Excellent
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9
Statistical Learning from a Regression Perspective (Springer Texts in
9.2
Excellent
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10
Interpretable Machine Learning: A Guide For Making Black Box Models Explainable
9.1
Excellent
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About Interpretable Machine Learning

Click here to learn more about these products.

Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples

Explainable AI with Python

Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps

Hands-On Explainable AI (XAI) with Python: Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps

Random Forests with R (Use R!)

Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms

Practical Threat Intelligence and Data-Driven Threat Hunting: A hands-on guide to threat hunting with the ATT&CK™ Framework and open source tools

Feature Engineering and Selection: A Practical Approach for Predictive Models (Chapman & Hall/CRC Data Science Series)

Statistical Learning from a Regression Perspective (Springer Texts in Statistics)

Interpretable Machine Learning: A Guide For Making Black Box Models Explainable

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