Data Science Artificial Intelligence

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.

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.

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.

This book walks you through the "need-to-know" aspects of artificial intelligence, including natural language processing, speech recognition, and the power of machine learning to show you how to make the most of this technology in a practical, tactical way. Case studies show how real-world companies are taking the next leap forward. Artificial intelligence and machine learning provide a data-driven basis for more robust and intensely-targeted marketing strategies - and companies that effectively utilize these latest tools will reap the benefit in the marketplace.

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.

This audiobook will help you get ready for the changes coming in the years ahead. Listen now. Packed with expert insights, the book addresses critical questions: How will AI alter employment, education, and global geopolitics? What ethical dilemmas will arise as humans interlace with AI through cyborgs and synthetic biology? Can we prepare for superintelligence and its utopian—or dystopian—outcomes?

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.

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.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a loan, how much we pay for insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: everyone is judged according to the same rules and bias is eliminated. And yet, as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated and incontestable, even when they're wrong. Most troubling, they reinforce discrimination.

Since the public release of Open AI’s ChatGPT, Google’s Bard, and other similar systems, some Members of Congress have expressed interest in the risks associated with “generative artificial intelligence (AI).” Although exact definitions vary, generative AI is a type of AI that can generate new content—such as text, images, and videos—through learning patterns from pre-existing data.

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.

Do you want to discover all the secrets of Big Data, Deep Learning, and everything in between? Have you ever asked yourself how can artificial intelligences learn from us? Do you want understand how does your smartphone personal assistant can understand you? In this guide, Artus Duval will show you everything you need to know about big data, machine learning, artificial intelligence, and its huge impact on our world; a swell as how to benefit from it 100 percent!

Artificial intelligence is transforming lives and revolutionizing industries. This accessible guide to generative AI and machine learning is for tech enthusiasts and forward-thinkers alike—whether you're in IT or a professional from another field looking to stay ahead and curious about AI’s impact on the future, this book provides the essential insights you need to stay competitive and informed in the Age of AI.

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.

En esta guía, aprenderá sobre todos los conceptos básicos de la inteligencia artificial. Aparte de eso, nos sumergiremos en algunos análisis de datos y ejemplos de inteligencia artificial. Cubriremos varios pasos en el proceso analítico y veremos qué se necesita para que la inteligencia artificial sea efectiva. Por último, pero no menos importante, los problemas de seguridad y privacidad saldrán a la luz, ya que la era de hoy está llena de piratería, espionaje y robo. Por lo tanto, es obligatorio que estos dispositivos y sistemas se mantengan seguros y protegidos.

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.

Machines are able to interpret and understand human beings, and also interpret the data that is fed to them because of artificial intelligence. So, what is artificial intelligence? If you have been reading the basics, you will know that artificial intelligence is a human being’s attempt to make a machine smart enough to handle processes that a human being would normally do. It is not easy to do this, since you will need to understand the system and also learn the required programming languages to instruct the computer to behave in the required manner.

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!

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.