Data Science Theory

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.

Unlock the power of data and artificial intelligence with the Fundamentals Series—a comprehensive two-book collection designed to equip you with the essential skills to succeed in today’s technology-driven world. Whether you’re looking to build a career in data analytics, harness the potential of AI, or monetize cutting-edge tools like large language models, this series provides the ultimate roadmap.

What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Drawing upon real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created.

In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally - hiring, driving, paying bills, even choosing romantic partners - that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology.

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.

Data Lake Architecture will explain how to build a useful data lake where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

We live in an incredible period in history. The computer revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before. But our love of computers should not cloud our thinking about their limitations. The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.

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.

Data science is the application of a combination of mathematical, statistical, analytical, and programming skills for the collection, organization, and interpretation of data to allow effective and proper management of the business whose data it is. It is a field where one should be trained and practiced. Without proper training and applicative skills, one cannot be as successful as a data scientist. There is a lot to learn about various data science tools and techniques. Getting certified will not only help you hone your skills but also will confirm your future as a data scientist.

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

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.

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.

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.

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.

If you've been following the news, you probably know that artificial intelligence is taking over. Self-driving trucks, face recognition, machines, and automatic cashiers are becoming the replacement for regular human beings. If you want to learn more about artificial intelligence, where it comes from, how some of it works, and what the future might look like, this audiobook is for you.

This book will open your eyes to the pitfalls of perception, and help you build a foundation for trust that elevates organizational performance... so you can make your data and AI initiatives succeed where others fail. Data, Strategy, Culture & Power is a must-listen for anyone who works with (or uses) data, analytics, and AI in today's complex organizations.

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.

According to historians, human beings have experienced the pre-industrial matter-based era (like the stone age) and the industrial energy-based era (like the steam age) in the past and now are experiencing the post-industrial information-based era (like the communication and information age). Based on this, we are living in the so-called ‘information age’ and information technology has put into our hands what was as a dream about a few decades ago. Indeed, we are living in an ‘ocean of information’ and ‘hunt’ what we need, from this ocean! This is a short outline of the main ...

If you need to learn how to use machine learning, big data, data science, and neural networks but you can’t (or there is no time to) study the complicated math and algorithms behind these technologies, then keep reading. All technologies related to artificial intelligence represent an incredible opportunity if you want to grow your business or if you are searching for a new job, but it’s not very easy to understand how they work.

In modern history, the story of capitalism has been a story of firms and financiers. That's all going to change thanks to the Big Data revolution. As Viktor Mayer-Schönberger, best-selling author of Big Data, and Thomas Ramge, who writes for The Economist, show, data is replacing money as the driver of market behavior. Big finance and big companies will be replaced by small groups and individual actors who make markets instead of making things: think Uber instead of Ford, or Airbnb instead of Hyatt. Will this be an age of prosperity or of calamity?