Formación | 🇬🇧 Training
Docker Succinctly
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.
Introduction to CNTK Succinctly (Microsoft Cognitive Toolkit)
“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)
Altair: Declarative Visualization in Python
Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understanding your data and its meaning. Altair’s API is simple, friendly and consistent and built on top of the powerful Vega-Lite JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code. Altair is developed by Jake Vanderplas and Brian Granger in close collaboration with the UW Interactive Data Lab.
Efficient R programming
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.
Deep Learning or Machine Learning? (MathWorks)
“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).









