Online or onsite, instructor-led live Chainer training courses demonstrate through interactive hands-on practice how to use Chainer to build and train neural networks in Python while making the code easy to debug.
Chainer 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. Plymouth onsite live Chainer trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Plymouth
Regus Drake Circus, Unit MSU9A, Level 1, Plymouth, united kingdom, PL1 1EA
Business travellers now have somewhere to work and meet while on the go – walk-in workspace at Drake Circus shopping centre...
Business travellers now have somewhere to work and meet while on the go – walk-in workspace at Drake Circus shopping centre in Plymouth. Our business lounge features flexible workspace and desks along with meeting rooms to rent by the day, half-day or hour.
Work smart and meet your clients in a professional environment. A virtual office service is also available. It’s easy to access by car and there’s plentiful parking at this site close to Plymouth University and the City Museum. The railway station is just 10 minutes away on foot.
• Fully-equipped meeting rooms
• Fully equipped private day offices
• Free high speed WiFi and refreshments
• Business class facilities – print, scan and copy documents
• Plentiful parking
• Walk in business lounge with flexible workspace to work productively
• Virtual offices – mail handling, business address & telephone answering
How to find us: We are located on Car Park Level 1/Food Court, next to The Entertainer Toy Shop.
This instructor-led, live training in Plymouth (online or onsite) is aimed at researchers and developers who wish to use Chainer to build and train neural networks in Python while making the code easy to debug.
By the end of this training, participants will be able to:
Set up the necessary development environment to start developing neural network models.
Define and implement neural network models using a comprehensible source code.
Execute examples and modify existing algorithms to optimize deep learning training models while leveraging GPUs for high performance.
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