First Steps with KERAS

2017-10-24T17:40:12+00:00 September 23rd, 2017|

First steps with KERAS In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. This post provides a fast-paced introduction to the KERAS API required to follow the DLAI Labs (Master Course at UPC - Autumn 2017). I will teach the part of DLAI course that will cover the basic principles of deep learning from computational perspectives. In this part we will review the basics of KERAS, a high-level neural networks API, written in Python and capable of running on top of [...]

First contact with Keras

2017-10-11T09:24:42+00:00 June 18th, 2017|

. . Keras is a Python library that provides a clean and convenient way to create a range of deep learning models on top of  powerful libraries such as TensorFlow, Theano (update about Theano) or CNTK. Keras was developed and maintained by François Chollet, a Google engineer and it is released under the permissive MIT license. Basic features of Keras (*) I value his austerity and simplicity, without frills approach and maximizing readability. It makes it possible to express neural networks in a very modular way, considering a model as a sequence or a graph alone. A good approximation for beginners, because the components of a Keras model are discrete elements that can be combined in arbitrary ways. New components are intentionally easy to add and modify within [...]