Course: Neural Computing for Industrial Applications
Richard Lister
listerrj at helios.aston.ac.uk
Wed Aug 7 06:56:32 EDT 1996
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Neural Computing for Industrial Applications:
An Intensive Hands-on Course
23-25 September 1996
Aston University
Birmingham
The Neural Computing Research Group at Aston University will be
running the course "Neural Computing for Industrial Applications - An
Intensive Hands-on Course" at Aston University between 23-25 September
1996. The course is aimed at applications developers as well as
technical managers in industry and commerce. It will also be of direct
relevance to practitioners in universities and research laboratories.
The course will focus on a principled, rather than ad-hoc, approach to
neural networks, providing the main tools to enable their successful
application in real-world problems. It combines lectures with
supervised laboratory sessions and aims to provide participants with a
coherent picture of the foundations of neural computing, as well as a
deep understanding of many practical issues arising in their
application to commercial tasks.
The lectures will take the student, step by step, throughout the
process of applying neural networks to commercial tasks including:
data preparation, choice of adequate configuration and cost function,
training, methods of performance improvement and validation. The
various development steps will be demonstrated on representative
regression and classification commercial tasks, emphasising their
relevance to real-world problems.
Lectures will cover both basic and advanced material ranging from
neural networks architectures and training methods to advanced
Bayesian methods and stochastic Monte-Carlo techniques for tackling
the difficulties of missing data, definition of error bars and model
selection.
Small group laboratory sessions will follow the lectures, providing a
demonstration of methods and techniques taught in class and a first
hand experience of their advantages and drawbacks for commercial
applications. In addition, the course will provide hands-on experience
in developing effective solutions to complex and challenging problems
using the Netlab software developed at Aston.
Who should attend
-----------------
This course is aimed at applications developers as well as technical
managers in industry and commerce. It will also be of direct relevance
to practitioners in universities and research laboratories.
Benefits
--------
The course will provide hands-on experience in developing effective
solutions to complex and challenging problems using the Netlab
software developed at Aston. Participants will receive a complimentary
copy of the Netlab software together with the Matlab simulation
environment. They will also receive lecture notes, laboratory manuals,
and a complementary copy of the new textbook "Neural Networks for
Pattern Recognition".
Laboratory sessions
-------------------
The course includes four practical sessions designed to complement and
reinforce the material presented during the lectures. These will make
use of commercial and industrial data sets and will be based on the
Netlab neural network simulation system running on modern Pentium PCs
under Microsoft Windows.
Course summary
---------------
The course begins with registration and a course dinner on Sunday 22
September and ends at 5.00pm on Wednesday 25 September.
Day 1
-----
The first day will include a general introduction to Neural Computing
from a statistical viewpoint, an introduction to the example data sets
used as case studies, data processing, the methodology of developing
an application, multi-layer perceptrons and training algorithms. Some
of the issues to be examined are
* Data preparation
Conventional techniques, feature extraction, dealing with
missing data, linear regression, PCA and visualisation.
* The multi-layer perceptron
Basic architecture, using MLP for regression problems.
* Training algorithms
On-line and batch learning, gradient descent and conjugate
gradient techniques, line search and other advanced
techniques.
A laboratory session for demonstrating and practising data processing
techniques introduced in the lectures will also be held in the
afternoon, making use of the example data sets introduced earlier.
Day 2
-----
After introducing the architecture and training algorithms for Radial
Basis Function networks, we will examine methods for monitoring and
controlling network performance including various validation and
regularisation techniques. The main topics include:
* Radial Basis Function Networks
Basic architecture, relation to conventional methods and
training paradigms.
* Generalisation
Training, validation and test sets, how to monitor training
success.
* Model complexity and regularisation
The Bayesian approach for controlling model complexity,
incorporating prior knowledge, error bars, the evidence
procedure and Monte Carlo methods.
Following the lectures, two laboratory sessions will be held during
the second day, demonstrating and practising training of MLP and RBF
networks as well as regularisation and validation methods.
Day 3
-----
The last day of the course will concentrate on extending the neural
networks framework presented for regression tasks to accommodate
classification problems. In addition we will discuss practical issues
related to using neural networks for commercial problems.
* Classification problems
Network predictions as probabilities and the Bayesian
approach, choice of error functions and activation functions,
minimising risk, reject option and imbalanced priors.
* Practicalities and diagnostics
Measures of performance assessment, error bars and input data
distribution, non-stationarity.
One laboratory session will be held in the last day, demonstrating the
use of MLP and RBF networks in classification tasks as well as
exercising the use of practical diagnostics methods.
Course tutors
-------------
Professor Christopher Bishop was formerly the Head of the Applied
Neurocomputing Centre at AEA Technology and has developed many
successful applications of neural networks in a wide range of domains.
He is Chairman of the Neural Computing Applications Forum.
Professor David Lowe was previously Leader of the Pattern Processing
Group at DRA Malvern, and is currently applying neural networks to
problems in electricity load demand forecasting, portfolio
optimisation, chemical vapour analysis and the control of internal
combustion engines.
Dr Ian Nabney worked on applications of neural computing for Logica
and is currently Programme Chair of the Neural Computing Applications
Forum. He has worked on applications of neural networks to jet engine
diagnostics, analysis of satellite radar signals, and control of
distillation columns.
Dr Richard Rohwer has research interests which include the Bayesian
and differential geometry views of machine learning, ultra-fast
memory-based algorithms, and practical methods for specification of
prior knowledge. He works with applications ranging from speech
processing to pipeline inspection.
Dr David Saad works on the foundations of neural computing from a
statistical mechanics perspective with emphasis on learning and model
selection, and has developed applications to problems in bar code
location and identification.
Dr Christopher Williams has developed novel approaches to pattern
recognition which extend conventional neural network methods, and also
has strong interests in applications to machine vision.
Enrolment Details
-----------------
Please send your booking form to the address below to reserve a place
on the course. Alternatively, you can reserve a place on the course by
accessing the enrolment form on our World Wide Web page at
http://www.ncrg.aston.ac.uk/. An invoice will be issued upon receipt
of this form and payment should be received by Friday 6th September
1996. Since the course involves laboratory classes, places are
strictly limited, so an early booking is strongly advised. Please
complete one form per delegate. A receipt will be issued upon payment
and will be sent together with an acknowledgement. Preparatory course
notes will be sent four weeks before the course date.
Cancellations
-------------
All cancellations must be received in writing. Cancellations made
before Friday 6th September 1996 will be subject to an administration
fee of UKP50, and cancellations made after this date will be subject
to the full amount of the course fee. Should a delegate become unable
to attend a substitution may be made, which must be confirmed in
writing.
What Payment Includes
---------------------
* Three days attendance on the course including laboratory sessions
and lectures.
* Free copy of Aston's Netlab neural network software (with
documentation).
* Full set of course notes and laboratory manuals.
* Free copy of the text book "Neural Networks for Pattern Recognition"
by Professor Christopher M Bishop.
* Attendance at the Course Dinner on Sunday 22nd September 1996.
* Buffet Lunches and refreshments on 23, 24, 25 September.
* Three nights Bed and Breakfast Accommodation at the Aston Business
School (delegates are free to make their own arrangements and a
reduced course fee is available).
Evening Meals
-------------
Evening meals on 23rd and 24th September can be taken at the Aston
Business School at a cost of UKP15 each. Please indicate on the
booking form if you would like either of these meals, and include
payment with your registration fee.
Software
--------
Participants will receive a complimentary copy of the Netlab software
and will be able to purchase Matlab (which is required to run Netlab)
at a special discounted rate. Matlab software is available on PC/MS-
Windows, Macintosh and UNIX platforms. Please indicate on the booking
form if you are interested in receiving further details about the
software.
Please complete and return this form to:
Miss H E Sondermann
Neural Computing for Industrial Applications
Neural Computing Research Group
Aston University
Birmingham
B4 7ET
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