Showing results for "Big data" in Programming & Software Development

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

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.

Computer programmers are increasingly in demand in the world. It is estimated that over 50 percent of companies fail to hire Python programmers because there are not enough advanced and prepared programmers. The problem, however, is that the world is full of books and technical courses that are not able to easily explain the Python programming language and teach how to analyze the data properly.

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.

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.

Machine Learning is now an essential component of many industrial uses and studies, but this field isn't exclusive to large businesses with extensive research crews. In case you are using Python, whilst a newcomer, this audiobook will educate you on practical methods to assemble your Machine Learning solutions. Considering all the current info available now, Machine Learning software is limited only by your imagination. You will study the steps required to generate a prosperous machine-learning application with Python and the sci-kit-learn library.

En un día promedio de principios del siglo xxi, los seres humanos que buscan en Internet acumulan ocho billones de gigabytes de datos. Esta asombrosa cantidad de información puede decirnos mucho sobre quiénes somos, los miedos, deseos y comportamientos que nos impulsan y las decisiones conscientes e inconscientes que tomamos. De lo profundo a lo mundano, podemos obtener un asombroso conocimiento sobre la psique humana que hace menos de veinte años parecía insondable.