Learn Data Science

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. 

Explosion of the economic relevance of data is related to: first, technological progress that has drastically reduced the costs of collecting and storing data; second, the advances in analytic techniques that have allowed for more advanced processing to extract greater value from available data. So, more value is extracted from exhausted data. Information generated for one purpose can and should be reused for another one, which means that data moves from primary to secondary uses. Data are more valuable over time.

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. 

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.

Your comprehensive guide to mastering The Data Component of your EOS Model—taking you from uncertain to unstoppable. Have you ever felt lost in knowing how your business is actually doing? Were you surprised by events that you didn’t see coming? Did you spend sleepless nights wondering...

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. 

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Artificial intelligence is the secret behind the big ones like Google, Facebook, Amazon, and we all know that. But it can also be a powerful tool in your own hands. With this audiobook, you will prepare the ground for your future success, either if you want to start up your own AI enterprise, apply your knowledge to your current business, or find a job at the greatest and most innovative companies. If programming will open you many doors, Python programming will open you even more.

From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The...

A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence Machine learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumour is cancerous, or deciding whether...

Harvard Business Review called data science “the sexiest job of the 21st century,” so it's no surprise that data science jobs have grown up to 20x in the last 3 years. With demand outpacing supply, companies are willing to pay top dollar for talented data professionals. However…To stand out in one of these positions, having foundational knowledge of interpreting data is essential.

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.

Martin Lindstrom, a modern-day Sherlock Holmes, harnesses the power of "small data" in his quest to discover the next big thing. Hired by the world's leading brands to find out what makes their customers tick, Martin Lindstrom spends 300 nights a year in strangers' homes, carefully observing every detail in order to uncover their hidden desires and, ultimately, the clues to a multimillion-dollar product.

The book wants to provide an analytical review of the implications of data in many different contexts. As a matter of fact, data are correlated to the legal, economic and personal contexts. Furthermore, the report presents the different perspectives concerning the usage of data and their impacts on the agents involved: data subject, data collector, and data processor. This in-depth analysis shows the importance of coordination among consumers, firms and policy makers.

Gain a competitive edge in today’s data-driven world and build a rich career as a data professional that drives business success and innovation… Today, data is everywhere… and it has become the essential building block of this modern society. And that’s why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems.

Data governance programs focus on authority and accountability for the management of data as a valued organizational asset. Non-Invasive Data Governance focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources.

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

This audiobook will not aim to be a manual in Python or programming in general but an incursion into the realm of these subjects - a short trip to make you curious about what Python and data analysis are all about, why they are used in association, and even how they are used, at times. If you are ready to embrace Python, even as a complete beginner, you are a daring soul who deserves to be part of the amazing future we’re building in this industry.

Data and Reality gracefully weaves the disciplines of psychology and philosophy with data management to create timeless takeaways on how we perceive and manage information. Although databases and related technology have come a long way since 1978, the process of eliciting business requirements and how we think about information remains constant.