Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples

Description

A deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including SHAP, feature importance, and causal inference, to build fairer, safer, and more reliable models. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Interpret real-world data, including cardiovascular disease data and the COMPAS recidivism scores Build your interpretability toolkit with global, local, model-agnostic, and model-specific methods Analyze and extract insights from complex models from CNNs to BERT to time series models Book DescriptionInterpretable Machine Learning with Python, Second Edition, brings to light the key concepts of interpreting machine learning models by analyzing real-world data, providing you with a wide range of skills and tools to decipher the results of even the most complex models. Build your interpretability toolkit with several use cases, from flight delay prediction to waste classification to COMPAS risk assessment scores. This book is full of useful techniques, introducing them to the right use case. Learn traditional methods, such as feature importance and partial dependence plots to integrated gradients for NLP interpretations and gradient-based attribution methods, such as saliency maps. In addition to the step-by-step code, you’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability. By the end of the book, you’ll be confident in tackling interpretability challenges with black-box models using tabular, language, image, and time series data.What you will learn Progress from basic to advanced techniques, such as causal inference and quantifying uncertainty Build your skillset from analyzing linear and logistic models to complex ones, such as CatBoost, CNNs, and NLP transformers Use monotonic and interaction constraints to make fairer and safer models Understand how to mitigate the influence of bias in datasets Leverage sensitivity analysis factor prioritization and factor fixing for any model Discover how to make models more reliable with adversarial robustness Who this book is for This book is for data scientists, machine learning developers, machine learning engineers, MLOps engineers, and data stewards who have an increasingly critical responsibility to explain how the artificial intelligence systems they develop work, their impact on decision making, and how they identify and manage bias. It’s also a useful resource for self-taught ML enthusiasts and beginners who want to go deeper into the subject matter, though a good grasp of the Python programming language is needed to implement the examples.

Get the book

Amazon.com

Search the book

eBay.com

Search the book

Other editions

• 

  Interpretable Machine Learning with Python: Learn to build interpretable high-performance...

  • 2021-03-26
  • 737 pages
  • Ebook
  • Packt Publishing Ltd

Similar books

• 

  Family History Digital Libraries

  By William Sims Bainbridge

  One named Sara and Timberlake had 11 male workers, 1 female worker, and 4 children workers, so it might have employed the Minor family.

• 

  Foundation Dreamweaver MX

  By Craig Grannell, Jerome Turner, Matt Stephens

  So here's what we need to do to arrive at our layout: s Create the main table to hold all the page elements. s Deal with the navigation area which is ...

• 

  Cisco CCNA Certification, 2 Volume Set: Exam 200-301

  By Todd Lammle

  This inclusive, two-book set provides what you need to know to succeed on the new CCNA exam. The set includes Understanding Cisco Networking Technologies: Volume 1 and the CCNA Certification Study Guide: Volume 2.

• 

  CompTIA Network+ Study Guide: Exam N10-006

  By Todd Lammle

  ... you can use: –a –A –c –n –r –R –S –s All nbtstat switches are case sensitive. Generally speaking, lowercase switches deal with NetBIOS names of hosts, ...

• 

  CompTIA Network+ Study Guide with Online Labs: N10-007 Exam

  By Todd Lammle, Jon Buhagiar

  ... you can use: –a –A –c –n –r –R –S –s All nbtstat switches are case sensitive. Generally speaking, lowercase switches deal with NetBIOS names of hosts, ...

• 

  CCNA: Cisco Certified Network Associate FastPass

  By Todd Lammle

  S The S reference point defines the point between the customer router and an ... with the letter E deal with using ISDN on the existing telephone network.

• 

  Stranger in the Chat Room

  By Todd Hafer, Jedd Hafer

  A sequel to In the Chat Room With God finds a group of teens contacted by a mysterious and increasingly malevolent character who claims to know about their encounters with the Almighty and challenges their beliefs. Original.

• 

  Error Correction Coding: Mathematical Methods and Algorithms

  By Todd K. Moon

  M M−1∑ k=0 −∞ ∞ k=0 The average energy per signal E s ∫ can be related to the ... we will deal primarily with additive white Gaussian noise (AWGN), ...

• 

  Security+ Training Guide

  By Todd King

  ... to deal with most , but unfortunately not all , of these potential threats . ... The S / MIME standard implements encryption for message content using ...

• 

  CCDA: Cisco Certified Design Associate Study Guide: Exam 640-861

  By Todd Lammle, Andy Barkl

  S reference point The S reference point defines the reference point between ... with the letter E deal with using ISDN on the existing telephone network.