Deep learning has already revolutionized machine learning research, but it remains out of reach for many developers. However, tools already exist today that enable leading-edge machine learning for many problem domains.
In this talk, we will go on an adventure to build a machine learning model that combines the benefits of linear models with deep neural networks. You will also gain some intuition about what is happening under the hood, and learn how to use this model for your own datasets! To accomplish this, we will use TensorFlow, an open-source machine learning library with a full Python interface. It has become the most popular machine learning library on GitHub, and the community around it is growing rapidly.