Phrases such as “machine learning” and “artificial intelligence” are thrown around so often by so many people, they risk becoming buzzwords along the lines of “Big Data.”
But unlike “Big Data,” which was always a somewhat-nebulous term, “machine learning” is a definitive process that, when applied correctly, can result in some impressive feats. For instance, check out how Google used it to radically transform the sophistication of Google Translate, one of its core services.
For those tech professionals who wish to break into machine learning and artificial intelligence, make no mistake about it: there’s a lot of education and training involved. Google wants to make that journey a little easier, though, with a new three-hour course that offers a quick overview of deep-learning fundamentals.
Deep learning is a methodology for building effective machine-learning models. Google’s course, available on its Google Cloud Platform Website, focuses on “a few basic network architectures, including dense, convolutional and recurrent networks, and training techniques such as dropout or batch normalization.” It features a few ways to solve “typical problems with neural networks,” and teaches some vocabulary and concepts related to A.I.
The course includes videos and slide decks, allowing you to learn the basic concepts on your own schedule. (And just to keep things interesting, some of those slide decks have some pretty funky cartoons, like the one above.)
The course is also an introduction to TensorFlow, Google’s deep-learning architecture. For those just starting to learn A.I.-related concepts, TensorFlow offers an open-source (under Apache 2.0) software library for numerical computation using data flow graphs. After constructing their graph, a user can write an inner loop that powers the aforementioned computation; in theory, it is easy to learn and deploy. (TensorFlow also helped create Google’s Parsey McParseface, if you want to see what a machine-learning toolkit is capable of building.)
The documentation for getting started with TensorFlow is available on a dedicated Website. Paired with lessons from Google, the platform could provide a suitable jumping-off point for an exploration of machine learning.