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Neural networks have been tremendously successful in a variety
of domains. Of course, they have also been extensively studied in
actuarial research and applied in insurance companies. For example,
an application which is highly relevant for life insurance is the
modeling and forecasting of mortality rates.
While simple feed-forward neural networks are already very
effective for a number of tasks, there are several techniques (such
as embedding layers or ensembles) and specialized architectures
(such as recurrent or convolutional neural networks) which are
necessary to exploit the full potential of these powerful machine
learning models.
Interpretability and explainability are often key requirements in
actuarial applications. Successful approaches in this direction
have been proposed and are, for example, based on combining neural
networks with the more traditional generalized linear models in the
so-called combined actuarial neural network or LocalGLMnet
architectures.
This web session is directed at anyone interested in
- modern approaches to mortality modeling
and forecasting using different kinds of neural networks,
- a broad overview of neural networks,
either to get familiar with the topic or as a refreshment and
expansion of existing knowledge.
Practical examples (using Jupyter, Keras and R) will be
presented and made available to the participants. Instructions on
how to install the necessary software will be provided to the
participants in advance.
Your early-bird registration fee is € 200.00 plus 19% VAT for
bookings by 29 December 2022. After this date, the fee will be €
270.00 plus 19% VAT.
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