As the Artificial Intelligence & Machine Learning Evangelist for EMEA, Julien focuses on helping developers and enterprises bring their ideas to life. He’s also actively blogging at https://medium.com/@julsimon. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in top-tier web startups where he led large Software and Ops teams in charge of thousands of servers worldwide. In the process, he fought his way through a wide range of technical, business and procurement issues, which helped him gain a deep understanding of physical infrastructure, its limitations and how cloud computing can help. Last but not least, Julien holds all seven AWS certifications.
Session: Deep Learning for Developers
The arcane jargon and intimidating equations of Deep Learning often discourage software developers, who wrongly think that they’re “not smart enough”. This talk will start with an explanation of how Deep Learning works. Then, through code-level demos based on Apache MXNet, we’ll demonstrate how to build, train and use models based on different network architectures (MLP, CNN, LSTM, GAN). Finally, you will learn about Amazon SageMaker, a new service that lets you train and deploy models into a production-ready hosted environment.
Workshop: End-to-end Machine Learning with Amazon SageMaker
In this workshop, we will use Amazon SageMaker to build, train and host Machine Learning models. Going through a number of Jupyter notebooks, you will first learn how to use built-in algorithms to perform complex tasks like image classification or clustering. Then, we’ll see how you can bring your own Tensorflow or Apache MXNet script to train Deep Learning models. Finally, you will deploy your models to SageMaker-maneged infrastructure and use them to predict new samples.