Kirjahaku

Georgia and Sam must save young Alice from the clutches of a man driven solely by corporate greed and a thirst for power. In a world where corporate greed is allowed to run wild, Roslun Global has become the largest pharmaceutical company in the world. As head of this juggernaut of a company, Richard Roslun wields unheard of global power. To obtain and hold onto this power, Roslun is willing to do anything, including killing innocents. When Richard Roslun realizes what he must do to save everything, his sights become set on a young girl named Alice. When Alice's mother returns home from work with an infection, all hell breaks lose in Alice's fragile world. Alice and her sister Georgia are hiding as death is literally banging on the front door when the unthinkable happens. A second outbreak tests the love between Sam Ashe and and his fianc Heather. Sam is a horror geek who has always been obsessed with zombies. When his fantasies become a reality, the man inside him will have to rise to the adventure ahead. Fate brings Sam and Georgia together in the mission to save young Alice. Will love be enough to fight off the undead and stop pure corporate greed?

Learn Docker "infrastructure as code" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller.It is not uncommon for a real-world data set to fail to be easily managed. The set may not fit well into access memory or may require prohibitively long processing. These are significant challenges to skilled software engineers and they can render the standard Jupyter system unusable. As a solution to this problem, Docker for Data Science proposes using Docker. You will learn how to use existing pre-compiled public images created by the major open-source technologies—Python, Jupyter, Postgres—as well as using the Dockerfile to extend these images to suit your specific purposes. The Docker-Compose technology is examined and you will learn how it can be used to build a linked system with Python churning data behind the scenesand Jupyter managing these background tasks. Best practices in using existing images are explored as well as developing your own images to deploy state-of-the-art machine learning and optimization algorithms.What You'll Learn Master interactive development using the Jupyter platformRun and build Docker containers from scratch and from publicly available open-source imagesWrite infrastructure as code using the docker-compose tool and its docker-compose.yml file typeDeploy a multi-service data science application across a cloud-based systemWho This Book Is ForData scientists, machine learning engineers, artificial intelligence researchers, Kagglers, and software developers