Presents: A Practical Introduction to the Keras API and TensorFlow Neural Networks
This presentation will cover some basic introductory theory at a very high-level, before introducing the Keras API implementation with practical worked examples written in Python and provided in Jupyter notebook format.
As well as examples on how to create simple TensorFlow “deep learning” neural networks with Keras, topics such as scaling up model building with large data-sets, monitoring model building progress and key parameters and concepts for building a neural network for various supervised learning use-cases.
This talk is pitched at an introductory / beginner level with respect to neural networks, but assumes Python experience and some basic machine learning knowledge.
Solution Architect for Relational Database, Analytics and Big Data platforms,specialising in multiple data processing and data analytics technologies.
Working with a range of business-verticals I help companies in sectors such as Banking and Life-Sciences transform their data-processing capabilities to optimise their businesses.