Titolo del corso:

Deep Learning

Obiettivi:

This course aims to present the mathematical, statistical and computational challenges of building stable representations for high-dimensional data, such as images, text and data. We will delve into selected topics of Deep Learning, discussing recent models from both supervised and unsupervised learning. Special emphasis will be on convolutional architectures, invariance learning, unsupervised learning and non-convex optimization.

Prerequisiti:

Basic Artificial Intelligence fundamental knowledge.

A chi è rivolto:

Technicians and software developers that are in charge of planning and operating deep learning systems.

Esercitazioni:

Development and Analysis of Deep Learning Apps using the most up-todate Deep Learning algorithm such as TensorFlow, Theano, Caffee, Keras, Torch.

Argomenti trattati:

Introduction to deep learning

Neural Networks

Convolutional Networks

Recurrent Nets

Deep learning models

Additional deep learning models

Deep learning platforms and software libraries

Deep Learning Framework: TensorFlow

Deep Learning Framework: Theano

Deep Learning Framework: Caffee

Deep Learning Framework: Keras

Torch

Livello:

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Durata: 3 giorni

Codice: KLA-DEEPL

Prossime date:

Modalità di Erogazione:

Instructor Led (ILT)
Live Virtual Training (LVT)
Blended (BLD)

Lingue:

Lingua Italiana English Language Langue Française Idioma Español

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