Semester: 3
ECTS: 6
Lectures: 30
Practice sessions: 30
Independent work: 120
Module Code: 23-02-543
Semester: 3
ECTS: 6
Lectures: 30
Practice sessions: 30
Independent work: 120
Module Code: 23-02-543

Module title:


Advanced machine learning


Module overview:


The objectives of this module are to enable students to:
• Interpret the definition of a range of neural network models.
• Be able to derive and implement optimisation algorithms for these models
• Interpret neural implementations of attention mechanisms and sequence embedding models and how these modular components can be combined to build state-­of-­the-­art NLP systems
• Be able to implement and evaluate common neural network models for language
• Interpret model selection process in order to describe a particular type of data
• Evaluate a learned model in practice
• Interpret the mathematics necessary for constructing novel machine learning solutions
• Be able to design and implement various machine learning algorithms in a range of real-world applications

Students learn to build and maintain machine learning models including deep learning models, today the most important machine learning method used in the world's most important production systems for various tasks. Through this module, students will acquire and implement basic deep learning techniques on examples from natural language processing such as machine translation, sentiment analysis, and recognition of named entities. Also, the module will handle deep and awarded learning.

It is important for students to take this module in order to enable students to deepen their understanding of mathematics and algorithms of deep neural architecture and deep learning, as well as acquire practical knowledge to implement deep learning. Students will acquire the skills of designing deep architecture in TensorFlow, as well as hand-made deep neural networks that can be implemented later in any programming language.



Literature:


Essential reading:
1. Skansi, S. (2018) Introduction to Deep Learning, Cham: Springer International Publishing,

Recommended reading:
2. Goodfellow, I., Bengio, Y., Courville, A. (2016) Deep Learning (Adaptive Computation and Machine Learning series), Cambridge: MIT Press, available at https://arxiv.org/abs/1609.08144