Abstract: In recent months, Deep Learning has become the hottest topic in the IT industry. However, its arcane jargon and its intimidating equations often discourage software developers, who wrongly think that they’re “not smart enough.” In this session, we’ll explain the basic concepts of Neural Networks and Deep Learning in simple terms, with minimal theory and math. Then, through code-level demos based on Apache MXNet, we’ll demonstrate how to build, train and use models based on different types of networks: multi-layer perceptrons, convolutional neural networks and long short-term memory networks. Finally, we’ll share some optimisation tips which will help improve the training speed and the performance of your models.
Bio: Before joining Amazon Web Services, Julien served for 10 years as CTO/VP Engineering in top-tier web startups. Thus, he’s particularly interested in all things architecture, deployment, performance, scalability and data. As a Principal Technical Evangelist, Julien speaks very frequently at conferences and technical workshops, where he meets developers and enterprises to help them bring their ideas to life thanks to the Amazon Web Services infrastructure.
Principal Evangelist ML/AI EMEA at Amazon