Heather Dawe – författare

Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfallsPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn ethical AI principles, frameworks, and governanceUnderstand the concepts of fairness assessment and bias mitigationIntroduce explainable AI and transparency in your machine learning modelsBook DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations.By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learnUnderstand explainable AI fundamentals, underlying methods, and techniquesExplore model governance, including building explainable, auditable, and interpretable machine learning modelsUse partial dependence plot, global feature summary, individual condition expectation, and feature interactionBuild explainable models with global and local feature summary, and influence functions in practiceDesign and build explainable machine learning pipelines with transparencyDiscover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platformsWho this book is forThis book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.

Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfallsPurchase of the print or Kindle book includes a free PDF eBook

Key Features

Learn ethical AI principles, frameworks, and governanceUnderstand the concepts of fairness assessment and bias mitigationIntroduce explainable AI and transparency in your machine learning models

Book Description

Responsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations.By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.

What you will learn

Understand explainable AI fundamentals, underlying methods, and techniquesExplore model governance, including building explainable, auditable, and interpretable machine learning modelsUse partial dependence plot, global feature summary, individual condition expectation, and feature interactionBuild explainable models with global and local feature summary, and influence functions in practiceDesign and build explainable machine learning pipelines with transparencyDiscover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platforms

Who this book is for

This book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.

In July 2014 the greatest cycle race in the world visited God’s Own County of Yorkshire. The 101st edition of the Tour De France started in Leeds and spent two days cycling over 240 miles through the county.Inspired by Yorkshire’s wonderful landscape and history A Bicycle Ride in Yorkshire is an illustrated guide to the route of Le Tour Yorkshire, by cyclist, writer and artist Heather Dawe. It is a guide to riding the route, to the sights and landscape seen along the way and to the rich cycling heritage found on Yorkshire’s roads.Beautifully illustrated with Heather’s paintings, the route is brought to life. On the first day Le Tour departed from Leeds into the rolling scenery of the Yorkshire Dales, past the breweries of Masham to finish in the spa town of Harrogate. Day two began in the historic city of York, from where it explored the industrial valleys of the South Pennines, skirting the Peak District before finishing in the steel city of Sheffield.A Bicycle Ride in Yorkshire is an essential read for any cycling, Tour de France or Yorkshire aficionado.

Winner: Mountain Literature (Non Fiction) The Jon Whyte Award, Banff Mountain Book Competition 2019Waymaking is an anthology of prose, poetry and artwork by women who are inspired by wild places, adventure and landscape.Published in 1961, Gwen Moffat’s Space Below My Feet tells the story of a woman who shirked the conventions of society and chose to live a life in the mountains. Some years later in 1977, Nan Shepherd published The Living Mountain, her prose bringing each contour of the Cairngorm mountains to life. These pioneering women set a precedent for a way of writing about wilderness that isn’t about conquering landscapes, reaching higher, harder or faster, but instead about living and breathing alongside them, becoming part of a larger adventure.The artists in this inspired collection continue Gwen and Nan’s legacies, redressing the balance of gender in outdoor adventure literature. Their creativity urges us to stop and engage our senses: the smell of rain-soaked heather, wind resonating through a col, the touch of cool rock against skin, and most importantly a taste of restoring mind, body and spirit to a former equanimity.With contributions from adventurers including Alpinist magazine editor Katie Ives, multi-award-winning author Bernadette McDonald, adventurers Sarah Outen and Anna McNuff, renowned filmmaker Jen Randall and many more, Waymaking is an inspiring and pivotal work published in an era when wilderness conservation and gender equality are at the fore.

With a back-story of running round the route of the classic Alpine journey the Tour de Mont Blanc, Heather Dawe explores the drive behind mountain running and racing, and how simply being in the mountains has inspired herself and other climbers, writers, artists and innovators through the years.

Mountain Stories is an illustrated memoir of journeys through some of Scotland’s most beautiful landscapes, including Skye's Cuillin, Knoydart, Assynt and the Far North. Writing during lockdown, author and artist Heather Dawe finds telling these stories a powerful means of reconnection with the mountains when they are physically inaccessible.Dawe's journeys are made by walking, running, cycling or sea-kayak. The stories are a reflection of the importance of wild places and the inspiration, art and culture associated with them.