Heavy-Lifting Using R Libraries - Udemy

In this video course, you will learn to tap some of the powerful abilities of R. R is one of the leading packages in the world with a vast number of active users and, as a result, has a massive number of state-of-the-art libraries. You will master the basics and get comfortable with R, so you can then use its libraries to do the heavy-lifting. You'll begin by looking at high-performance computing in the classic, computationally intensive scenario: finding prime numbers.Then you'll learn how to use R, before moving on to using C++, which is far faster. Next you will use the power of parallel, though that varies from problem to problem since some are more suitable for parallelization. Then you will look at some powerful options available on R where you don't just produce a static result but instead respond to user selections. This will be a small sample of the countless alternatives out there. Having learnt that there are exciting things going on in data science, you can now begin your journey in whatever specialized niche you wish. Don't stop here, this is just the start. There are active R communities on the internet and many Packt books and courses to take you to where you want to go!

About the Author

Dr. Samik Sen is a theoretical physicist and loves thinking about hard problems. After his PH.D., in developing computational methods to solve problems for which no solutions existed, he began thinking about how to tackle math problems while lecturing. He developed algorithms to generate problem sets and solutions and learned how to create video lessons. He has since developed a large Facebook community teaching school math around Ireland, with associated e-learning products and a YouTube channel. Samik is currently fascinated by machine- and deep-learning, which seem to be world-changing on the scale of Calculus. He has been developing a machine-learning system to do this, which has begun doing better than he could himself (this was his original intention), spotting structures he'd never heard of. He has a YouTube channel associated with data science, which also provides a valuable engagement with people round the world who look at problems from a different perspective.