ADVANCED MACHINE LEARNING
The module will focus on the implementations of various machine learning techniques and their applications in various domains. The primary tools used in the class are the Python programming language and several associated libraries.
KNOWLEDGE DISCOVERY
This module covers the fundamental concepts of deep learning methods and how to use them for extracting, modelling and visualizing the learned knowledge.
Topics include: neural networks with backpropagation, convolutional neural networks, recurrent neural networks, methods for representation learning, and how to use them under different learning regimes (supervised, unsupervised and reinforcement learning) and in variety of real-world applications ranging from computer vision, machine translation and medical image analysis.
The learning objectives are:
to understand and use the main methodologies and techniques for learning from data
to understand the main methodologies to design and implement neural networks for real-world applications
to understand how to extract and learn knowledge in scenarios when supervision cannot be provided
to understand and foresee the reliability of machine learning methods in operational scenarios.
Knowledge and understanding
To understand the main concepts of learning from data
To understand concepts and tools for building intelligent systems using supervision and no supervision
To understand the most important machine learning and artificial intelligence methodologies and techniques used by industries to make sense of data in order to support the decision process
To understand what are the most appropriate techniques to be used in different real-world applications
Applying knowledge and understanding
To be able to effectively understand and use the main tools for creating, loading and manipulating datasets.
To design and implement from scratch a machine learning system following application-derived constraints in terms of modelling and data
To understand proper benchmarks and baselines and analysing achieved results and their generalization in real-world applications
To be able to apply methodologies and techniques to analyse data.