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Description:

Deep learning is currently one of the hottest areas in data science. Increasingly, businesses are applying it to gain competitive advantage. According to Gartner, eighty percent of data scientists will have deep learning in their toolkits by 2018. There is lot of demand for it, but not enough practitioners. In this webcast, we will set the foundation for what deep learning is, then walk through what it takes to train and deploy a production-quality neural network.

In this webcast you will learn:

• Common use cases for deep learning in business
• What neural networks are and, more important, how they are trained and deployed in practice
• How data scientists can design an optimal neural network when a single training run can take two weeks
• Some popular deep learning frameworks like TensorFlow, Caffe, PyTorch, Keras
• How GPUs are used in training deep learning models
• Free resources to get you started on your deep learning journey

About Anthony Stevens, Offering Manager, Watson Machine Learning

Anthony Stevens is offering manager for Watson Machine Learning where he collaborates with IBM Watson Research to translate theory into practice. Previously, Anthony was a senior Watson architect working with over 40 customers including partners, engineering, and research teams to architect cognitive solutions using Watson technologies.

Anthony is an expert in transforming complex problems and datasets into elegant mobile, web, and cloud solutions. He has done this for life science, health, consumer, and multimedia companies by bringing deep expertise in both software development and product management. He has led the process to design, architect, build, and launch products for startups and Fortune 500 corporations.

As a top 20 winner of the first Android Developer Challenge in 2008, Google awarded him $125,000 for building an innovative product that showcased Android. In short, you can consider him a Master Builder.