The Masters Series – Deep Learning Uncovered
With Dr. Kevin McGuinness
Recent developments in machine learning approaches, collectively referred to as deep learning, are responsible for the large performance gains made in the last decade in tasks such as voice recognition, image and video classification, and forecasting. Deep learning refers to a set of generative machine learning techniques that autonomously generate high-level representations from raw data sources, and using these representations perform machine learning tasks such as classification, regression, clustering, and content generation. Deep learning techniques work especially well with unstructured data sources such as images, text, or time series.
Through real world examples, discussions, and live code demonstrations this one-day workshop, designed for analytics professionals, introduces the most important deep learning techniques for supervised and unsupervised machine learning tasks.
Register Your Interest Now
Info and Costs
Date : Tuesday 28th April & Thursday 30th April
Time : 9.30am – 1pm
Duration : 1 day
Price : €325
Discounts are available for multi-class passes.
Location : Online Classroom
Should I Attend?
If you are familiar with fundamental concepts in data manipulation, descriptive statistics, and machine learning and want to know more about Deep Learning, this Master Class is for you. 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 keras). 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 deep learning techniques, and an understanding of how they should be applied to build real-world-relevant solutions. After completing the workshop delegates you be able to:
- Frame business problems as deep learning problems and solve them using appropriate techniques
- Understand the basic structure of artificial neural networks
- Understand gradient descent and the back-propagation of error algorithm
- Appreciate the complications involved in building deep neural networks
- Understand how to apply appropriate deep learning techniques (e.g. convolutional neural networks) to image understanding problems (e.g. classification and segmentation)
- Understand how to apply appropriate deep learning techniques (e.g. recurrent neural networks) to text understanding problems (e.g. classification and translation)
Dr. Kevin McGuinness
Dr Kevin McGuiness is an Assistant Professor with the School of Electronic Engineering in Dublin City University and a Science Foundation Ireland Funded Investigator at the Insight Centre for Data Analytics and in the ENABLE research programme.
His primary research interests are computer vision, deep learning, image and video segmentation, segmentation evaluation, machine learning, content-based multimedia information retrieval, and human-computer interaction.