I'm a programmer and technical author at Octopus Deploy and I'm deeply interested in DevOps. Since the 1950s, people have been studying software delivery in search of better ways of working. We’ve seen many revolutions since Lincoln Labs first introduced us to phased delivery, with lightweight methods transforming how we wrote software at the turn of the century. My interest in DevOps goes beyond my enthusiasm for methods in general, because we now have a great body of research that adds to our empirical observations on the ways we work.
Before Agile and Lean had rocked the software development industry, William Deming was busy forging this new world of work.
Out of the Crisis is predominantly a management book, but it’s really the spark that started the lightweight movement in software delivery. A key concept in the book is how to identify the work system's performance, separate from the performance of individuals.
Essential reading for managers and leaders, this is the classic work on management, problem solving, quality control, and more—based on the famous theory, 14 Points for Management
In his classic Out of the Crisis, W. Edwards Deming describes the foundations for a completely new and transformational way to lead and manage people, processes, and resources. Translated into twelve languages and continuously in print since its original publication, it has proved highly influential. Research shows that Deming’s approach has high levels of success and sustainability. Readers today will find Deming’s insights relevant, significant, and effective in business thinking and practice. This…
I have been studying neoliberal political economy and its future transformations since I wrote Rationalizing Capitalist Democracy. One major insight has been the deep entanglement of neoliberal political-economic practices with de facto power relations. The liberal normative bargaining characterizing Adam Smith’s Wealth of Nations yields to coercive bargaining in which threats of harm are the surest and best means to get one’s way. If one seeks to understand how systems will evolve when governed by strategic competition, then orthodox game theory is useful. However, if one seeks to live in a post-scarcity society in which genuine cooperation is possible, then we can enact solidarity, trust-based relationships, and collective moral accountability.
In order to be moral and responsible agents, our will must be free in the sense that we make choices animated by our individual consciences. Much of the neoliberal consumer world uses big data sets and our personalized digital fingerprints in order to cater to our every wish and desire, and to sell merchandise. Research shows that individuals disregard ethical responsibility when they believe that humans are not free, and that we are instead governed by innate drives and biological functions. Mele challenges recent research that uses cognitive science to argue that the human will is not free and instead exists as an illusion. This book provides a deep analysis of why we have grounds to be confident that we can act freely, governed by our internal beliefs, commitments, and goals.
Does free will exist? The question has fueled heated debates spanning from philosophy to psychology and religion. The answer has major implications, and the stakes are high. To put it in the simple terms that have come to dominate these debates, if we are free to make our own decisions, we are accountable for what we do, and if we aren't free, we're off the hook.
There are neuroscientists who claim that our decisions are made unconsciously and are therefore outside of our control and social psychologists who argue that myriad imperceptible factors influence even our minor decisions to the…
I was stimulated by Norbert Wiener’s “Cybernetics” to study circuits in the brain that control behavior. For my graduate studies, I chose the olfactory bulb for its experimental advantages, which led to constructing the first computer models of brain neurons and microcircuits. Then I got interested in how the smell patterns are activated when we eat food, which led to a new field called Neurogastronomy, which is the neuroscience of the circuits that create the perception of food flavor. Finally, because all animals use their brains to find and eat food, the olfactory system has provided new insights into the evolution of the mammalian brain and the basic organization of the cerebral cortex.
The other books in this series are mostly about the real brain. But artificial intelligence promises us a new enhanced brain. What does the future hold? Terrence Sejnowski is a neuroscientist who was one of the first to realize the potential of AI. Since he has been there from the start, in this book he gives the reader an exciting inside story on the people and the advances that are reshaping our lives.
Early attempts at AI were limited, but once computational power took off big computers running multilayer neural nets began proving that they could defeat humans at the most demanding games, enhance human capabilities such as pattern recognition, text recognition, language translation, and driverless vehicles, and work to obtain rewards, just like a human. While these advances are dramatic, it is well to remember that the networks are built not from representations of real neurons, but rather from…
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
I’m the Science Director of the Science Museum Group, based at the Science Museum in London, and visiting professor at the Dunn School, University of Oxford, and Department of Chemistry, University College London. Every time I write a book I swear that it will be my last and yet I'm now working on my ninth, after earlier forays into the physics of Christmas and the love life of Albert Einstein. Working with Peter Coveney of UCL, we're exploring ideas about computation and complexity we tackled in our two earlier books, along with the revolutionary implications of creating digital twins of people from the colossal amount of patient data now flowing from labs worldwide.
Over a single year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, exchanged hand-drawn postcards to chart the granular details of their lives using clusters, plots, and graphs. We featured the outpourings of these talented “information designers” in a 2016 Science Museum exhibition on big data and these striking images, in turn, paved the way for their book, Dear Data, which provides a remarkable portrait of these artists. An intimate and human take on big datathat invites us all to ponder how to represent our own lives.
From an award-winning project comes an inspiring, collaborative book that makes data artistic, personal - and open to all
Each week for a year, Giorgia and Stefanie sent each other a postcard describing what had happened to them during that week around a particular theme. But they didn't write it, they drew it: a week of smiling, a week of apologies, a week of desires.
Presenting their fifty-two cards, along with thoughts and ideas about the data-drawing process, Dear Data hopes to inspire you to draw, slow down and make connections with other people, to see the world through a…
I’m an Associate Professor in the University of Alabama’s Department of Philosophy. I worked as an FBI Special Agent before making the natural transition to academic philosophy. Being a professor was always a close second to Quantico, but that scene in Point Break in which Keanu Reeves and Patrick Swayze fight Anthony Kiedis on the beach made it seem like the FBI would be more fun than academia. In my current position as a professor at the University of Alabama, I teach in my department’s Jurisprudence Specialization. My primary research interests are at the intersection of philosophy of law, political philosophy, and criminal justice. I’ve written three books on policing.
I love this book because it reminds us of the many ways that technology can affect justice.
It is tempting to think sophisticated tactics such as “predictive policing” can solve all problems relating to human bias. However, Brayne shows that data and algorithms do not eliminate bias and discretion. Instead, high-tech police tools simply make bias less overt and visible, which erodes the public’s ability to hold the police accountable.
I especially enjoyed how the book flips the script, considering diverse ways to use these tools to help the public. For example, how can municipalities use technology to analyze the underlying factors that contribute to policing problems in the first place?
The scope of criminal justice surveillance, from the police to the prisons, has expanded rapidly in recent decades. At the same time, the use of big data has spread across a range of fields, including finance, politics, health, and marketing. While law enforcement's use of big data is hotly contested, very little is known about how the police actually use it in daily operations and with what consequences.
In Predict and Surveil, Sarah Brayne offers an unprecedented, inside look at how police use big data and new surveillance technologies, leveraging on-the-ground fieldwork with one of the most technologically advanced law…
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
When can we trust a forecast? Given how often forecasts end up being very wide of the mark, a degree of scepticism might well be warranted. Paul Goodwin provides an entertaining account of forecasting, arguing that intuition may serve us well in some settings, but that computer-based analysis of big data might be expected to prevail in others.
Whether it's an unforeseen financial crash, a shock election result or a washout summer that threatens to ruin a holiday in the sun, forecasts are part and parcel of our everyday lives. We rely wholeheartedly on them, and become outraged when things don't go exactly to plan.
But should we really put so much trust in predictions? Perhaps gut instincts can trump years of methodically compiled expert knowledge? And when exactly is a forecast not a forecast? Forewarned will answer all of these intriguing questions, and many more.
Packed with fun anecdotes and startling facts, Forewarned is a myth-busting guide…
I am motivated by working on products that many people use. I've been a part of companies that deliver products impacting millions of people. To achieve it, I am working in the Big Data ecosystem and striving to simplify it by contributing to Dremio's Data LakeHouse solution. I worked on projects using Spark, HDFS, Cassandra, and Kafka technologies. I have been working in the software engineering industry for ten years now, and I've tried to share my experience and lessons learned in the Software Mistakes and Tradeoffs book, hoping that it will allow current and the next generation of engineers to create better software, leading to more happy users.
The Hands-on Machine Learning book presents an end-to-end approach to many problems that can be solved with machine learning.
Every concept and topic is backed up with a running code that you can experiment with and adapt to your real-world problems.
Thanks to this book, you will be able to understand the state of the art of today's machine learning and feel comfortable using the most up-to-date ML methods.
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout…
I am a leader in analytics and AI strategy, and have a broad range of experience in aviation, energy, financial services, and the public sector. I have worked with several major organizations to help them establish a leadership position in data science and to unlock real business value using advanced analytics.
Not everybody needs to be a data scientist, but everybody does need to be data literate. Without an intentional focus on evangelism and building a strong data culture in your organization it will be an uphill battle to make meaningful change. This book helps individuals and leaders to understand what data literacy is, and how we can build it like any other skill.
In the fast moving world of the fourth industrial revolution not everyone needs to be a data scientist but everyone should be data literate, with the ability to read, analyze and communicate with data.
It is not enough for a business to have the best data if those using it don't understand the right questions to ask or how to use the information generated to make decisions. Be Data Literate is the essential guide to developing the curiosity, creativity and critical thinking necessary to make anyone data literate, without retraining as a data scientist or statistician.
With learnings to show…
I’m a journalist and a tinkerer. I’m fascinated not only by how things work but by how small levers can move mountains. Growing up in the workshop of my grandfather, an old Boston boatwright, I was mesmerized by the idea that a small rudder could maneuver a huge vessel. In college, I fell in love with how a small idea or expression could redirect a course of research or a country. As a self-taught maker of things, I appreciate how technologies empower us. I’ve chosen these books because they’re examples of how small ideas become things, lines of research, or patterns of thinking that shift human progress in unknowable ways.
I love gutsy books by outsiders, and Ms. Saxena, as a woman of color working in the Ivy League and the worlds of artificial intelligence and Big Data, is very much an outsider.
That makes her deep knowledge and insights into how AI and Big Data are changing business even that much more interesting. Plus, this is one of the only books I’ve read that explains how artificial intelligence works in a clear, direct way that doesn’t assume the reader already knows about things like machine learning and neural nets.
Have you heard about artificial intelligence (AI) and big data but felt they are technologies too big or too complicated for you or your business? Do you imagine AI as a Hollywood science fiction stereotype or something in the far and distant future?
Take heart. AI is none of those things. It's part of our everyday lives, and it has the power to transform your business.
This book will put AI, big data, the cloud, robotics, and smart devices in context. It will reveal how these technologies can dramatically multiply any businesses-including yours-by strategically using your data's latent, transformative potential.…
I would like to consider myself an experienced and successful designer, researcher, and educator. I'm an Associate Professor in Communication Design and the Head of Education for the School of Design at Northumbria University in the United Kingdom, where I've taught and researched for the last twenty years so I'm super passionate about this subject and love explaining how design works. Before joining academia, I worked internationally as a designer and creative director for numerous prestigious design and media organizations, including Philips, Time-Warner, Windmill Lane Pictures, and WPP in the UK, Ireland, USA, and Southeast Asia. Working in these different businesses and locations gave me a broad perspective on the role and importance of design.
There is so much understandable suspicion about how organisations use or misuse your personal data that it's hard to see the many potential benefits of data sharing. This book restores a little faith in technology and those who develop it for public benefit.
It is a compelling read, learning how data can be used for good and bad, with many references to the author’s personal journey, from working in customer services to being an internet entrepreneur before becoming a researcher.
'An essential read' Diane Coyle, University of Cambridge
'We are currently living in a moment of extreme pessimism about data. This book will change your mind.'
It's impossible to escape digital technology. And with that comes fear. But whatever the news has told you about data and technology, think again. Data expert and tech insider turned Cambridge researcher Sam Gilbert shows that, actually, this data revolution could be the best thing that ever happened to us.
Good Data examines the incredible new ways this information explosion is already helping us - whether that's…
