Languages and Libraries for Machine Learning Udacity


R is a purpose-built language meant for statistical computing, and is a clear winner for large-scale data-mining, visualization and reporting. You have easy access to a huge collection of packages (through the CRAN repository) that enable you to apply almost all kinds of Machine Learning algorithms, statistical tests and analysis procedures. The language itself has an elegant--albeit esoteric--syntax for expressing relationships, transforming data and performing parallelized operations.

Google getting serious about deep learning – Publishes free three month course


Google is getting ready for deep learning and it wants you to be ready as well, which is why the tech giant has launched a three month course in order to help you learn its next level machine language. Deep learning is a machine learning technique that has become the foundation of the several services that Google already provides (this would include everything from speech recognition to automatically sorting your photo collection). The course is definitely not for absolute beginners, but it aims to help established engineers and data scientists get on par with deep learning as well as TensorFlow. In a blog post published on Udacity, Google's principal scientist Vincent Vanhoucke, who is also the course's primary instructor, has said that the aim to make deep learning will become more accessible in this manner.

Intro to Machine Learning Udacity


You'll learn how to start with a question and/or a dataset, and use machine learning to turn them into insights. Behind any great machine learning project is a great dataset that the algorithm can learn from. Regressions are some of the most widely used machine learning algorithms, and rightly share prominence with classification. In this case, that means identifying the most important features of your data.