Published By: IBM APAC
Published Date: May 14, 2019
IBM PowerAI Enterprise helps to make deep learning easier and faster for organizations by bringing together some of the most popular open source frameworks for deep learning, with development and management tools in a single installable package. Designed to simplify end-toend deep learning, PowerAI Enterprise allows enterprises to spend less time on data preparation, implementation and integration, and more time training neural networks for results. IBM PowerAI Enterprise version 1.1.2 includes the most popular deep learning frameworks in one installation:
- BVLC Caffe
- Keras (tensorflow-keras)
Published By: Infoblox
Published Date: Jun 18, 2015
This in-depth white paper from the SANS institute will bring you up to speed on today’s most dangerous vulnerability. In it, you will learn about:
• How DNS works, and why, if unprotected, it can put your network at risk
• The different kinds of DNS attacks—and who’s been hit by them
• Major compliance frameworks that address the problem
• Effective governance and best practices
Advances in deep neural networks have ignited a new wave of algorithms and tools for data scientists to tap into their data with artificial intelligence (AI). With improved algorithms, larger data sets, and frameworks such as TensorFlow, data scientists are tackling new use cases like autonomous driving vehicles and natural language processing. Read this technical white paper to learn reasons for and benefits of an end-to-end training system. It also shows performance benchmarks based on a system that combines the NVIDIA® DGX-1™, a multi-GPU server purpose-built for deep learning applications and FlashBlade, a scale-out, high performance, dynamic data hub for the entire AI data pipeline.
Sybase PowerBuilder has remained throughout the years a bastion of application development productivity for a wide class of enterprise applications that combine database access with a highly productive graphical user interface (GUI).
Advances in deep neural networks have ignited a new wave of algorithms and tools for data scientists to tap into their data with artificial intelligence (AI). With improved algorithms, larger data sets, and frameworks such as TensorFlow, data scientists are tackling new use cases like autonomous driving vehicles and natural language processing.
Advances in deep neural networks have ignited a new wave of algorithms and tools for data scientists to analyze and action data using artificial intelligence (AI). Financial services companies can greatly benefit from this leap forward in technology that enables unique insights into all aspects of the industry. With improved algorithms, larger data sets, and frameworks such as TensorFlow, data scientists now have the ability to tackle complex problems and find credible and profitable solutions.
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