Online or onsite, instructor-led live Apache MXNet training courses demonstrate through interactive hands-on practice how to use Apache MXNet to build and deploy a deep learning model for image recognition.
Apache MXNet training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Apache MXNet trainings in Swansea can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Swansea
Princess House, Princess Way, Swansea, united kingdom, SA1 3LW
The Princess House Centre is located in the heart of Swansea with panoramic views over the city, Swansea Bay and the Gower ar...
The Princess House Centre is located in the heart of Swansea with panoramic views over the city, Swansea Bay and the Gower area of outstanding natural beauty. These offices are in a prime location and have recently undergone a major refurbishment. Swansea is an inspiring place to do business in a superb natural environment. It is Wales' second largest city and the regional shopping, leisure, cultural, education and administrative centre for south west Wales. In recent years, it has experienced dramatic economic growth generated by a structured investment programme. This has transformed the city into a modern economy dominated by the service sector, which is estimated to employ about 86 per cent of the local workforce. Swansea is now home to a wide range of national and international companies in the financial, telecommunications and technology industries and is fast building a reputation as a city of innovation with a significant knowledge-based economy.
This instructor-led, live training in (online or onsite) is aimed at data scientists who wish to use Apache MXNet's to build and deploy a deep learning model for image recognition.
By the end of this training, participants will be able to:
Install and configure Apache MXNet and its components.
Understand MXNet's architecture and data structures.
Use Apache MXNet's low-level and high-level APIs to efficiently build neural networks.
Build a convolutional neural network for image classification.
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