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. Liege onsite live Torch trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Liège, Place des Guillemins
NobleProg Liège, 2 Place des Guillemins, Liège, Belgium, 4000
Luik is de hoofdstad van de provincie Luik en de economische hoofdstad van Wallonië. Door het aantal inwoners is het de eers...
Luik is de hoofdstad van de provincie Luik en de economische hoofdstad van Wallonië. Door het aantal inwoners is het de eerste Waalse agglomeratie, de derde agglomeratie van België na Brussel en Antwerpen en de vierde gemeente na Antwerpen, Gent en Charleroi. Luik is lange tijd een grote industriestad geweest, maar sinds de jaren zestig heeft het een lange neergang ondergaan, waarbij de fabrieken in verval raken. Luik is ook sterk afhankelijk van transport en multimodaliteit. Luik is een belangrijk economisch centrum met zijn autonome haven, de tweede binnenhaven in West-Europa en zijn luchthaven gespecialiseerd in vracht. In feite blijft de stad de economische hoofdstad van Wallonië.
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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