Data Science Theory

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.

This new edition introduces operation and design techniques for Sigma-Delta converters in physical and conceptual terms, and includes chapters which explore developments in the field over the last decade. Includes information on MASH architectures, digital-to-analog converter (DAC) mismatch and mismatch shaping

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

Decision intelligence (DI) has been widely named as a top technology trend for several years, and Gartner reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies. But until now, there has been little practical guidance for organizations to formalize decision making and integrate their decisions with data. With this book, authors L. Y. Pratt and N. E. Malcolm fill this gap.

Fuelled by a surge of migration to cities, the country's growth appears to be defined by urbanisation and by its growing, prosperous middle class. It is also defined by progressive and liberal young Indians, who vote beyond the constraints of identity, and paradoxically, by an unchecked population explosion and rising crimes against women. Is it, though?

Celebrated data-driven growth leader Lillian Pierson delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.

Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service within the Microsoft Azure cloud computing platform.

Welcome to the exciting world of AI-powered trading bots for executing options trades. In this subchapter, we will explore the fundamentals of AI and option trading, providing you with a solid foundation to begin your journey into the world of trading stocks and options. Whether you are a novice trader looking to learn the basics or an experienced investor seeking to leverage the power of AI technology in your trading strategies, this subchapter is designed to help you understand the key concepts and principles that drive success in the world of option trading.

The ultimate guide of how-to templates with real-world examples that demystify the art and science of AI prompt writing, offering clear frameworks, proven templates, and step-by-step instructions. This empowering guide reveals the exact formulas behind successful prompts with structured templates, troubleshooting guides, and practical exercises. Develop the critical thinking skills needed to achieve consistent, high-quality AI outputs.

In Behavioral AI: Unleash Decision Making with Data, behavioral economist Dr. Rogayeh Tabrizi delivers an intuitive roadmap to help organizations disentangle the complexity of their data to create tangible and lasting value. The book explains how to balance the multiple disciplines that power AI and behavioral economics using a combination of the right questions and insightful problem solving.

The Inclusion Equation is a comprehensive, one-of-a-kind guide to merging DEI and employee wellbeing concepts with data analytics and AI. In this book, renowned thought leader and professional keynote speaker Dr. Serena H. Huang explains exactly how to quantify the effectiveness of new talent strategies by connecting them to a firm ROI estimate, enabling listeners to approach and win the favor of higher-ups in any organization with the same effectiveness that marketing and financial departments do.

In our highly competitive world of today, we need all the edge we can to get ahead of our competitors. For a long time, companies have focused on spending more on marketing and advertisement, ignoring the powerful asset they had at their disposal: data. Although this isn't the case anymore for large companies, smaller businesses are still in the dark about this, and you can use this asset to your advantage. This bundle will show you how.

In this accessible and comprehensive audiobook, we start from scratch, assuming no prior knowledge. Each chapter is carefully crafted to guide you through the fundamental concepts and practical applications of AI, including machine learning, generative AI, and deep learning. With clear and plain English explanations, you'll be surprised at how quickly you can start thinking and speaking fluently in the words and mindset of an AI expert!

A team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

We are in the 4th industrial revolution; companies need to figure out how to survive. In this exciting revolution, machine intelligence has had a more unprecedented impact on business than the internet, and it's the only path to corporate survival in the future... Leaders don't have to be scientists to unlock the power of AI technology that is already radically altering the industrial landscape. If you're ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.

Whether you're new to the world of programming and are looking for clarity on what direction to take, or you're simply curious about what machine learning, AI, and big data has in store for the future and want to prepare for it, this guide makes it easy to actually understand implement machine learning and data analytics effectively.

Un científico de datos es alguien que sabe más de informática que un estadístico, y conoce más estadísticas que un científico de la computación. Si bien, en gran medida, esto es cierto, convertirse en un buen científico de datos requiere el dominio no solo de estas dos áreas clave, sino también de algunas teorías y modelos cruciales para este campo. El libro se recomienda a todos los lectores interesados ​​que aspiran a destacarse en el campo de la ciencia de datos.

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.

One of the most peculiar and possibly unique features of humans is the vast amount of information we carry outside our biological selves. But in our rush to build the infrastructure for the 20 quintillion bits we create every day, we’ve failed to ask exactly why we’re expending ever-increasing amounts of energy, resources, and human effort to maintain all this data. Drawing on deep ideas and frontier thinking in evolutionary biology, computer science, information theory, and astrobiology, Caleb Scharf argues that information is, in a very real sense, alive - an aggregate lifeform.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.