Deep learning in the enterprise: Opportunities and challenges

Tools, frameworks, access to high-value data, and practical approaches to deployment and integration with existing systems and applications are just some of the considerations facing companies adopting deep learning. Ron Bodkin explores tools, open source technology, frameworks, and strategies to cost-effectively achieve strategic results with deep learning in the enterprise.

High-impact deep learning applications from machine translation to self-driving cars are capturing the world’s attention, and enterprises have begun to deploy deep learning to unlock new opportunities and achieve competitive and strategic advantage. The potential impact of these initiatives in the next few years has the potential to redefine industries and establish new winners and losers. However, the challenges enterprises face in implementing deep learning in a practical and strategic manner are significant. Tools, frameworks, access to high-value data, and practical approaches to deployment and integration with existing systems and applications are just some of the considerations. Ron Bodkin explores tools, open source technology, frameworks, and strategies to cost-effectively achieve strategic results with deep learning in the enterprise. Topics include: