ADVANCED MACHINE LEARNING - DEEP LEARNING

The application of machine learning is deepening and widening in the world of business and technology. Among different machine learning algorithms, deep learning stands out. Since its introduction in 2006, deep learning has fulfilled some of the oldest artificial intelligence promises, such as autonomous/driverless vehicles, machine translation, precise and speaker-independent speech recognition, and robust visual object recognition. Deep learning systems have even beaten the human experts in their field and achieved remarkable performances. In this course, we will address the what, why and how of deep learning. What is deep learning? Why do we need deep learning? And how do we apply and harness the benefits of deep learning in business cases? We will focus on the three popular deep learning algorithms, namely Convolutional Neural Networks (CNN), Long/Short Term Memories (LSTM), and Generative Adversarial Networks (GAN), and their applications. The methods and platforms for implementation and evaluation of deep learning systems would be discussed. Furthermore, learners will practise employing deep learning to deal with a few applied examples using Python and Octave environments.