Artificial Intelligence & Deep Learning

08:30 - 09:30 Uhr: Registration with Tea & Coffee

09:30 - 09:45 Uhr: WELCOME & INTRODUCTION

09:45 - 10:30 Uhr: ACCELERATING AI FROM THE CLOUD TO THE EDGE

This session will cover Intel’s vision for Artificial Intelligence and introduce the latest Intel® portfolio of Hardware, Software and Services from a software development and AI perspective. Besides the architectural details of the latest Intel® Xeon® Scalable processor family, we will also cover the whole spectrum of hardware solutions up to the recently announced Intel® Nervana™ Neural Network Processor (NNP).
Ralph De Wargny, Intel

10:30 - 11:00 Uhr: Coffee break

11:00 - 11:45 Uhr: AI CONCEPTS AND USE CASES

In this session, we will explore the concepts and applications of Deep Learning, with a focus on real world applications using the Intel® CPUs for training and inference.
Francois Fayard, Bayncore

11:45 - 12:30 Uhr: INTEL® NERVANA™ SOFTWARE STACK – OVERVIEW & IMPLEMENTATION

This session will cover Intel® Nervana™’s software stack for AI, Machine Learning and Deep Learning: from low-level libraries like MKL / MKL-DNN, CPU-optimized frameworks (incl. neon, Caffe, TensorFlow, Theano), development tools like VTune, the Intel® Python* distribution, to the new Intel® Nervana™ Graph library (ngraph)
Stephen Blair-Chappell, Bayncore

12:30 - 13:45 Uhr: Lunch break & Exhibition

13:45 - 14:15 Uhr: MEET THE ENGINEERS

14:15 - 14:45 Uhr: OPTIMIZING PYTHON CODE USING THE INTEL® DISTRIBUTION OF PYTHON*

It used to be the case that you would never use the words ‘performance’ and ‘python in the same sentence. The Intel® Distribution of Python* changes all that. In this second of a two-parts’ session we show how you can speed up you Python codes ‘out-of-the-box’ by using the Intel® Distribution of Python*.  In this session we use the Intel® optimized version of SciKit-Learn.
Francois Fayard, Bayncore

14:45 - 15:45 Uhr: PRACTICAL FRAMEWORKS SESSION 1: USING TENSORFLOW*

In this tutorial, we show how to use the Intel®-optimized version of TensorFlow* hosted on the high-level neural networks library Keras. As well as demonstrating of how to use these frameworks, the session will include an explanation of how the Intel® implemented optimizations were achieved.
Francois Fayard, Bayncore

15:45 - 16:00 Uhr: Short coffee break

16:00 - 17:30 Uhr: PRACTICAL FRAMEWORKS SESSION 2: END-TO-END DEVELOPMENT USING INTEL® OPTIMIZED CAFFE AND THE  MOVIDIUS™ NEURAL COMPUTE STICK

In this session, we discuss the advantages of using Caffe optimized for Intel® Architecture and show how to train deep network models using one or more compute nodes. We then show how these pre-trained models can be deployed on the Movidius™ Neural Compute Stick.
Roger Philip, Bayncore; Vishnu Madhu, Intel

17:30 - 18:00 Uhr: Q&A and closing comments

JETZT ANMELDEN