Data Science Theory

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.

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.

If you want to learn about data science, then pay attention...This audiobook will discuss everything that you need to know when it comes to working in the field of data science. There is so much that we can explore and learn about when it comes to the world of data science, and this ultimate guide is here to help you navigate through these specialties. You will see just how important the ideas of data mining, data analytics, and even artificial intelligence are to our world as a whole today.

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. The job of such a scientist is trending all over the world. The demand for such scientists is huge, more than the number of available candidates. A recent report explained that the need for these scientists has increased by more than 50 percent since last year.

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. The job of such a scientist is trending all over the world. The demand for such scientists is huge, more than the number of available candidates. Data science is a field of study that is growing at a fast pace. From big tech companies to E-commerce companies to websites and many others are now relying on data science.

Yes, you can succeed in an AI-driven world by unleashing your potential in machine learning! A working knowledge of AI and ML is no longer a “nice-to-have” but an “essential” in today's job market. But what if you feel lost amid the tech jargon? What if terms like “algorithms”, “neural networks”, or “data preprocessing” sound like a foreign language to you?

As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion.

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.

Alex Vail took a sabbatical from his job on the board of one of the country's leading manufacturers to conduct several research projects, including the largest ever study into the UK's corporate AI capabilities. In total, he surveyed 234 senior leaders and interviewed 92 executives from FTSE350 companies to identify why digital transformations succeed or fail; the data dependency of organisations; and their levels of data literacy at senior levels.

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.

Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. Today data is the vital raw material of the information economy. The explosive abundance of this digital asset, more than doubling every two years, is creating a new world of opportunity and challenge. Data-ism is about this next phase, in which vast, Internet-scale data sets are used for discovery and prediction in virtually every field. It is a journey across this emerging world with people, illuminating narrative examples, and insights.

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.

Lars Nielsen and Noreen Burlingame provide a brief, understandable, user-friendly guide to all aspects of Data Science. The authors address the various skills required, the key steps in the Data Science process, software technology related to the effective practice of Data Science, and the best rising academic programs for training in the field.

Harness the power of machine learning to revolutionize your business, even if you're new to programming or tech concepts. Do you dream of integrating machine learning into your business model but find the subject overwhelming? Are you unsure how these cutting-edge technologies can be applied to your entrepreneurial ventures? Do you struggle to stay updated with rapid advancements in machine learning, fearing that you may fall behind?

"The AI Awakening: A New Era of Data Discovery and Growth" by Dr. Mozhgan Tavakolifard explores the transformative potential of artificial intelligence in business and personal growth. Bridging cutting-edge technology with human-centric values, it offers a unique perspective on leveraging AI for innovation, sustainable growth, and human potential enhancement.

Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you'll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python's scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web.

Models are at the centre of everything we do. They act as metaphors that help us better understand the increasingly complex problems facing us in the modern world. Yet in recent years, the validity of the models we use has been hotly debated and there has been renewed awareness of the disastrous consequences when the makers and interpreters of models get things wrong. Drawing on contemporary examples from finance, climate and health policy, Erica Thompson explores what models are, why we need them, how they work and what happens when they go wrong.

Machines are able to interpret and understand human beings and also interpret the data that is fed to them because of artificial intelligence (AI). So, what is artificial intelligence? If you have been trying to learn the basics of artificial intelligence, you will know that it is a human being’s attempt to make a machine smart enough to handle processes that a human being would normally do.

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?

The goal of this book is simple: provide a perfect insight into data science from scratch. It clearly explains the difference between data science and big data, explaining the concept of big data very concisely and clearly. Operations on data are also very clearly explained in this audiobook. The book is also an ultimate guide to master data mining and data-analytic.