Science des données

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value.

By the end of on average day in the early 21st century, human beings searching the Internet will amass eight trillion gigabytes of data....

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm....

Knowing how to craft SQL queries and navigate your way around a database is an essential skill if are a Database Administrator, System Administrator, or Programmer...

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. The audiobook offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data....

Understanding Ethereum now could equip you with the knowledge ahead of a major technological revolution in these early stages of development....

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns....

In The Legal Singularity, Abdi Aidid and Benjamin Alarie argue that the proliferation of artificial intelligence-enabled technology is on the verge of radically reconfiguring the law, our institutions, and our society for the better....

Data analysis is a skill that becomes essential as the world becomes more data-driven. And one of the most effective ways to dive into data analysis is by learning a programming language. Python is a great place to start. This book explains what you need to know to start using it for data analysis.

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion.