Michael Munn – författare

Wherever we are in the quality movement, there is more to discover--to explore. Today, quality serves business as a way of increasing profits. That is one end of a spectrum. Tomorrow, quality takes business into the rest of the spectrum. In this new dimension, business learns to serve, and be served, from a foundation of unconditional love. At the other end of the spectrum is quality's far-reaching goal--the attainment of harmony between people and the entire cosmos. This goal reveals the gap, and steps, between it and what we do today.This book is intended for explorers and pioneers. It is not for those who are comfortable in today's paradigms. It is for those who search and yearn for new ways bring heart into the world of business and society. It is not for those who are comfortable living an unexamined and changeless life. It is for those who sense a thrill in the heart with the changes of each new day.Experience, not dry learning, is the heart of this book. For this reason, "Practical Exercises" are included in most of the chapters. They are experiences of things that can be known, but not told or taught. Without the exercises, your knowing will be superficial. With them, you can enter into dimensions unknown to you today.Michael W. Munn, Ph.D., heads the Gaia Center for Quality in Palo Alto, California. He provides keynotes, experiential change seminars, and business quality workshops. Strategic planning, executive development, proposal, and reengineering efforts are among the topics of his workshops.

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.

In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.

You''ll learn how to:

Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure models are treating users fairly

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.

In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.

You''ll learn how to:

Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure models are treating users fairly

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does.

Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you''ll be able to apply these tools more easily in your daily workflow.

This essential book provides:

A detailed look at some of the most useful and commonly used explainability techniques, highlighting pros and cons to help you choose the best tool for your needsTips and best practices for implementing these techniquesA guide to interacting with explainability and how to avoid common pitfallsThe knowledge you need to incorporate explainability in your ML workflow to help build more robust ML systemsAdvice about explainable AI techniques, including how to apply techniques to models that consume tabular, image, or text dataExample implementation code in Python using well-known explainability libraries for models built in Keras and TensorFlow 2.0, PyTorch, and HuggingFace

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does.

Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you''ll be able to apply these tools more easily in your daily workflow.

This essential book provides:

A detailed look at some of the most useful and commonly used explainability techniques, highlighting pros and cons to help you choose the best tool for your needsTips and best practices for implementing these techniquesA guide to interacting with explainability and how to avoid common pitfallsThe knowledge you need to incorporate explainability in your ML workflow to help build more robust ML systemsAdvice about explainable AI techniques, including how to apply techniques to models that consume tabular, image, or text dataExample implementation code in Python using well-known explainability libraries for models built in Keras and TensorFlow 2.0, PyTorch, and HuggingFace

Most intermediate-level machine learning books usually focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance and the need to be able to explain why and how your ML model makes the predictions that it does. This practical guide brings together the best-in-class techniques for model interpretability and explains model predictions in a hands-on approach. Experienced ML practitioners will be able to more easily apply these tools in their daily workflow.

No legend ever walked taller than Hollywood icon John Wayne. Now, author Michael Munn''s startling new biography sets the record straight on why Wayne didn''t serve in World War II, on director John Ford''s contribution to Wayne''s career, and the mega-star''s highs and lows: three failed marriages, and two desperate battles with cancer. Munn also discloses publicly, for the first time, Soviet dictator Josef Stalin''s plot to assassinate Wayne because of his outspoken, potentially influential anti-Communist views. Drawing on time spent with Wayne on the set of Brannigan- and almost 100 interviews with those who knew him-Munn''s rare, behind-the-scenes look proves this "absolute all-time movie star" was as much a hero in real life as he ever was on-screen.

Wherever we are in the quality movement, there is more to discover--to explore. Today, quality serves business as a way of increasing profits. That is one end of a spectrum. Tomorrow, quality takes business into the rest of the spectrum. In this new dimension, business learns to serve, and be served, from a foundation of unconditional love. At the other end of the spectrum is quality''s far-reaching goal--the attainment of harmony between people and the entire cosmos. This goal reveals the gap, and steps, between it and what we do today.This book is intended for explorers and pioneers. It is not for those who are comfortable in today''s paradigms. It is for those who search and yearn for new ways bring heart into the world of business and society. It is not for those who are comfortable living an unexamined and changeless life. It is for those who sense a thrill in the heart with the changes of each new day.Experience, not dry learning, is the heart of this book. For this reason, "Practical Exercises" are included in most of the chapters. They are experiences of things that can be known, but not told or taught. Without the exercises, your knowing will be superficial. With them, you can enter into dimensions unknown to you today.Michael W. Munn, Ph.D., heads the Gaia Center for Quality in Palo Alto, California. He provides keynotes, experiential change seminars, and business quality workshops. Strategic planning, executive development, proposal, and reengineering efforts are among the topics of his workshops.

Wherever we are in the quality movement, there is more to discover--to explore. Today, quality serves business as a way of increasing profits. That is one end of a spectrum. Tomorrow, quality takes business into the rest of the spectrum. In this new dimension, business learns to serve, and be served, from a foundation of unconditional love. At the other end of the spectrum is quality''s far-reaching goal--the attainment of harmony between people and the entire cosmos. This goal reveals the gap, and steps, between it and what we do today.This book is intended for explorers and pioneers. It is not for those who are comfortable in today''s paradigms. It is for those who search and yearn for new ways bring heart into the world of business and society. It is not for those who are comfortable living an unexamined and changeless life. It is for those who sense a thrill in the heart with the changes of each new day.Experience, not dry learning, is the heart of this book. For this reason, "Practical Exercises" are included in most of the chapters. They are experiences of things that can be known, but not told or taught. Without the exercises, your knowing will be superficial. With them, you can enter into dimensions unknown to you today.Michael W. Munn, Ph.D., heads the Gaia Center for Quality in Palo Alto, California. He provides keynotes, experiential change seminars, and business quality workshops. Strategic planning, executive development, proposal, and reengineering efforts are among the topics of his workshops.

Wherever we are in the quality movement, there is more to discover--to explore. Today, quality serves business as a way of increasing profits. That is one end of a spectrum. Tomorrow, quality takes business into the rest of the spectrum. In this new dimension, business learns to serve, and be served, from a foundation of unconditional love. At the other end of the spectrum is quality's far-reaching goal--the attainment of harmony between people and the entire cosmos. This goal reveals the gap, and steps, between it and what we do today. This book is intended for explorers and pioneers. It is not for those who are comfortable in today's paradigms. It is for those who search and yearn for new ways bring heart into the world of business and society. It is not for those who are comfortable living an unexamined and changeless life. It is for those who sense a thrill in the heart with the changes of each new day.Experience, not dry learning, is the heart of this book. For this reason, "Practical Exercises" are included in most of the chapters. They are experiences of things that can be known, but not told or taught. Without the exercises, your knowing will be superficial. With them, you can enter into dimensions unknown to you today.Michael W. Munn, Ph.D., heads the Gaia Center for Quality in Palo Alto, California. He provides keynotes, experiential change seminars, and business quality workshops. Strategic planning, executive development, proposal, and reengineering efforts are among the topics of his workshops.

Many of the stars of the silver screen in twentieth-century Hollywood became national icons, larger-than-life figures held up as paragons of American virtues. Unfortunately, the private lives of actors such as John Wayne, Henry Fonda, and Errol Flynn rarely lived up to the idealistic roles they portrayed. However, James Stewart was known as the underdog fighter in many of his films and in real life. He was highly decorated for his bravery during his time as a bomber pilot during World War II and was adored for his earnest and kindly persona.Here many unknown sides of Stewart are revealed: his explosive temper, his complex love affairs, his service as a secret agent for the FBI, his innate shyness, and his passionate patriotism. Munn’s personal touch shines through his writing, as he was a friend of Stewart and his wife, Gloria, and interviewed them as well as their colleagues and friends. This definitive biography reveals the childhood ups and downs that formed this cinema hero, explores the legendary Fonda–Stewart relationship, and recounts Stewart’s experiences making acclaimed films that include The Philadelphia Story, Rear Window, Anatomy of a Murder, It’s a Wonderful Life, and Mr. Smith Goes to Washington.

In the summer of 1970 McQueen and author Michael Munn took a road trip in England while the actor’ s film Le Mans was on hold. McQueen told stories of being a kid on the street, petty theft, rolling drunks, gangs and losing his virginity to a whore who took cakes in exchange for sexual favours.Munn met McQueen on other occasions, last speaking in 1980, and in this poignant, personal account, recalls the story of one of the greatest American anti-heroes of all time. Dubbed the King of Cool, his life was anything but. His childhood was hard – he rarely attended school and didn’ t like to sleep at home where his mother entertained men. Full of anger, the young McQueen suffered trying to control it – indeed, it became part of his acting persona. He once stole a knife from a butcher’ s store and went home to kill his mother and stepfather.McQueen spent time in a school for wayward children and joined the merchant navy, escaping to become a towel boy in a brothel in the Dominican Republic, before returning to the US to steal cars and break into stores and houses. He joined the Marines before finally falling into acting.This is the fascinating story of McQueen from boyhood to American superstar: a complicated man who could be difficult to work with but also a delight, have many famous lovers yet be paranoid and jealous. The author has interviewed a host of stars and directors to get closer to the true character of this extraordinary man.