The Masters Series – Reinforcement Learning
with Dr Brian Mac Namee

The combination of classical methods and new deep learning models has led to a resurgence in attention to reinforcement learning. Reinforcement learning has been used to achieve state of the art performance in tasks ranging from game playing, to machine learning model training itself, to practical deployments in the healthcare, retail, finance, and energy industries. This course will explore the most important semi-supervised machine learning techniques and explore their applications and how they can be put to practical use.

Through real world examples, discussions, and live code demonstrations this one-day workshop, designed for analytics professionals, introduces the most important reinforcement learning techniques and how they can be used to develop and deploy real-world solutions.

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Info and Costs

Date : Tuesday 20th October and Thursday 22nd October

Time : 9.30am – 1 pm

Duration : 1 day

Price : €325
Discounts are available for multi-class passes.

Location : Online Classroom

Should I Attend?

To attend this Master Class you should be familiar with fundamental concepts in data manipulation, descriptive statistics, and machine learning. Specifically, you should be comfortable building and evaluating classification models (using techniques such as logistic regression, decision trees, support vector machines or random forests). The live code demonstrations during the workshop will use the Python programming language and relevant Python packages (e.g. pandas, scikit-learn, and kerasRL). While familiarity with these is not required it would be useful. A list of specific functionalities with which you should be familiar, and suggested online revision materials, will be circulated before the workshop.

What will I Learn?

This workshop has been designed to equip you with the most important reinforcement learning techniques, and an understanding of how they should be applied to build real-world-relevant solutions. After completing the workshop you will be able to:

  • Understand the fundamentals of reinforcement learning
  • Frame problems to be solved using reinforcement learning
  • Develop reinforcement learning agents using popular tools
  • Understand the fundamental ideas behind reinforcement learning systems
  • Understand the temporal difference learning approach to reinforcement learning and how it uses deep learning models
  • Implement deep reinforcement learning systems
  • Understand modern developments in deep reinforcement learning such as model-based learning and policy gradient  methods.

The Master
Dr. Brian Mac Namee

Dr. Brian Mac Namee, Director of Training at Krisolis, has over two decades of experience in data analytics lecturing, training, research, and consultancy. With particular expertise in analytics fundamentals, Brian has delivered analytics training nationally and internationally for world-leading organisations as well as mentored analytics teams at companies ranging from large multi-nationals to small start-ups.

As an academic, Brian manages a group of researchers focusing on analytics and regularly presents and publishes both nationally and internationally on their work. His research interests lie in the areas of artificial intelligence, machine learning, predictive analytics, and data visualisation. He is a co-author of the textbook “Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies” published in 2015 with MIT Press. Brian is Director of the Science Foundation Ireland funded Centre for Research Training in Machine Learning.