Libros digitales
The R programming language on its own is a powerful tool that can perform thousands of statistical tasks, but by writing programs in R, you gain tremendous power and flexibility to extend its base functionality. Senior Succinctly series author and editor James McCaffrey shows you how in R Programming Succinctly.
In a company, when the business process is defined, employees feel confident in their roles. They understand expectations and can easily identify when something is amiss or requires escalation. In Business Process Flow Mapping Succinctly, Erica Quigley will show you the activities that should occur in order to completely define a business process so you can identify and rectify gaps in communication, procedures, and teams. You will also learn a simple way to document the process so the project team working with you can feel confident in what they are being asked to execute.
Containers have revolutionized software development, allowing developers to bundle their applications with everything they need, from the operating system up, into a single package. Docker is one of the most popular platforms for containers, allowing them to be hosted on-premises or on the cloud, and to run on Linux, Windows, and Mac machines. With Docker Succinctly by Elton Stoneman, learn the basics of building Docker images, sharing them on the Docker Hub, orchestrating containers to deliver large applications, and much more.
“Microsoft CNTK (Cognitive Toolkit, formerly Computational Network Toolkit), an open source code framework, enables you to create feed-forward neural network time series prediction systems, convolutional neural network image classifiers, and other deep learning systems. In Introduction to CNTK Succinctly, author James McCaffrey offers instruction on the basics of installing and running CNTK, and also addresses machine-learning regression and classification techniques. Exercises and explanations are included in each chapter”. (Syncfusion)
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively-until now.
“In this ebook, we discuss some of the key differences between deep learning and traditional machine learning approaches. We look at three factors that might influence your decision and then step through an example that combines the two approaches”. (MathWorks).
