Deep Learning

This program is an introduction to concepts and applications in Deep Learning, including various kinds of Neural Networks for supervised and unsupervised learning.

Goal
The students will learn about:
 fundamental concepts of Deep Learning, including various Neural Networks for supervised and unsupervised learning,
 building, training, and deploying different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders,
 application of Deep Learning to real-world scenarios such as object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers,
 Master Deep Learning at scale with accelerated hardware and GPUs,
 using of popular Deep Learning libraries such as Keras, PyTorch, and Tensorflow applied to industry problems.

Organizer
IBM

E-learning

More information

The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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