Data Science Theory

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues. Discover two comprehensive manuscripts in one audiobook.

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

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.

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.

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.

Data science gets thrown around in the press like it's magic. Major retailers are predicting everything, from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. Data science is little more than using straightforward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will teach how you how that's done within the familiar environment of a spreadsheet.

Mastering data science doesn’t have to be complicated. Data Science 2020 can help you go from novice to expert in no time at all. To keep up with this growing industry, one has to know all the ins and outs, be able to keep up with the fast-moving innovations, and really understand all the nuances of this field. In this audiobook, you will not only learn what data science is but you will learn all the variables included with it.

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.

Mastering data science doesn’t have to be complicated. Data Science 2020 can help you go from novice to expert in no time at all. To keep up with this growing industry, one has to know all the ins and outs, be able to keep up with the fast-moving innovations, and really understand all the nuances of this field. In this audiobook, you will not only learn what data science is but you will learn all the variables included with it.

In Fusion Strategy, world-renowned innovation guru Vijay Govindarajan and digital strategy expert Venkat Venkataraman offer a first-of-its-kind playbook that will help industrial companies combine what they do best-create physical products-with what digitals do best-use algorithms and AI to parse expansive, interconnected datasets-to make strategic connections that would otherwise be impossible.

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.

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.

From one of the world’s leading data scientists, a landmark tour ofthe new science of idea flow, offering revolutionary insights into the mysteries of collective intelligence and social influence.

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.

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.

Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.

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.

Would you like to learn to use Python extracting meaningful insight from data to grow your business but you reckon it will be too complex? As a beginner, you will be probably afraid that programming is difficult. Learning data analysis and data mining can take months, and the possibility to give up before mastering them could be high. The best solution is a complete programming manual with hands-on projects and practical exercises. This guide is structured as a course with seven chapters for seven days and studied special exercises to apply what you learned step-by-step.