Programme

Deep Learning (DNN)

Deep neural networks for image, speech and language intelligence at scale.

Business Intelligence & Analytics Lab (BIAL)

DEEP LEARNING (Deep Neural Network)

Artificial intelligence is growing exponentially. There is no doubt about that. Deep learning is an aspect of artificial intelligence (AI) that is concerned with emulating the learning approach that human beings use to gain certain types of knowledge. At its simplest, deep learning can be thought of as a way to automate predictive analytics. While traditional machine learning algorithms are linear, deep learning algorithms are stacked in a hierarchy of increasing complexity and abstraction.

But the further AI advances, the more complex become the problems it needs to solve. And only Deep Learning can solve such complex problems and that's why it's at the heart of Artificial intelligence.

What you’ll learn

Course curriculum

Unsupervised Learning

Reinforcement Learning

Artificial Neural Networks to solve a Customer Churn problem

Convolutional Neural Networks for Image Recognition

Recurrent Neural Networks to predict Stock Prices

Self-Organizing Maps to investigate Fraud

Boltzmann Machines to create a Recommender System

Understand the intuition behind Artificial Neural Networks

Apply Artificial Neural Networks in practice

Understand the intuition behind Convolutional Neural Networks

Apply Convolutional Neural Networks in practice

Understand the intuition behind Recurrent Neural Networks

Apply Recurrent Neural Networks in practice

Understand the intuition behind Self-Organizing Maps

Apply Self-Organizing Maps in practice

Understand the intuition behind Boltzmann Machines

Apply Boltzmann Machines in practice

Understand the intuition behind AutoEncoders

Apply AutoEncoders in practice

Supervised Learning

Tensorflow and Pytorch

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