Online or onsite, instructor-led live Torch training courses demonstrate through interactive hands-on practice the principles and unique features of Torch, and how it can be applied in real-world applications.
Torch 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. Truro onsite live Torch trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Truro - Commercial Street
1 Commercial St., Truro, Canada, B2N 3H8
Build your business with a flexible office space in Truro, the Hub of Nova Scotia. Commute easily to this ideal location usin...
Build your business with a flexible office space in Truro, the Hub of Nova Scotia. Commute easily to this ideal location using the nearby Truro Station, and if you’re driving, Trunk 2 and Trunk 4 highways intersect in the town.
Torch is an open source machine learning library and a scientific computing framework based on the Lua programming language. It provides a development environment for numerics, machine learning, and computer vision, with a particular emphasis on deep learning and convolutional nets. It is one of the fastest and most flexible frameworks for Machine and Deep Learning and is used by companies such as Facebook, Google, Twitter, NVIDIA, AMD, Intel, and many others.
In this instructor-led, live training, we cover the principles of Torch, its unique features, and how it can be applied in real-world applications. We step through numerous hands-on exercises all throughout, demonstrating and practicing the concepts learned.
By the end of the course, participants will have a thorough understanding of Torch's underlying features and capabilities as well as its role and contribution within the AI space compared to other frameworks and libraries. Participants will have also received the necessary practice to implement Torch in their own projects.
Format of the Course
Overview of Machine and Deep Learning
In-class coding and integration exercises
Test questions sprinkled along the way to check understanding
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