10-22-2001
I just finished HPUX SysNet I training, and
am taking SysNet II this week.
The place mentioned by Jerzey is in Phoenix.
(44st & 202).
But is can be very expensive for an individual
to take. It can be about $2000 -$3000 depending
on what you take. I concur, you can learn Fundamentals
on your own. Load Linux on a machine, and learn to move
around in the system. RedHat for Dummies, (which comes witha copy of RedHat) is an excellent start.
Once you think you got a grip on the basics, you have 3 choices:
1) Find a job that will pay to send you to HP training.
2) Pay for the classes, then pay for the test.
3) By a book on HP-UX Sytem Admin & Networking, pay for the
test, and become certified.
My suggestion if for a combination of 2 & 3
Take SysNet 1, then buy a book, refresh what you learned,
and learn the rest. Then take the test. I took the practice test
near the end of SysNet1 and passed, so if you think logically, you won't have a problem.
Good Luck,
For contact information for GE Access, email me...
RECON
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LEARN ABOUT PHP
fann_cascadetrain_on_data
FANN_CASCADETRAIN_ON_DATA(3) 1 FANN_CASCADETRAIN_ON_DATA(3)
fann_cascadetrain_on_data - Trains on an entire dataset, for a period of time using the Cascade2 training algorithm
SYNOPSIS
bool fann_cascadetrain_on_data (resource $ann, resource $data, int $max_neurons, int $neurons_between_reports, float $desired_error)
DESCRIPTION
The cascade output change fraction is a number between 0 and 1 determining how large a fraction the fann_get_MSE(3) value should change
within fann_get_cascade_output_stagnation_epochs(3) during training of the output connections, in order for the training not to stagnate.
If the training stagnates, the training of the output connections will be ended and new candidates will be prepared.
This training uses the parameters set using the fann_set_cascade_..., but it also uses another training algorithm as it's internal train-
ing algorithm. This algorithm can be set to either FANN_TRAIN_RPROP or FANN_TRAIN_QUICKPROP by fann_set_training_algorithm(3), and the
parameters set for these training algorithms will also affect the cascade training.
PARAMETERS
o $ann
-Neural network resource.
o $data
-Neural network training data resource.
o $max_neurons
- The maximum number of neurons to be added to neural network.
o $neurons_between_reports
- The number of neurons between printing a status report. A value of zero means no reports should be printed.
o $desired_error
- The desired fann_get_MSE(3) or fann_get_bit_fail(3), depending on which stop function is chosen by fann_set_train_stop_func-
tion(3)
RETURN VALUES
Returns TRUE on success, or FALSE otherwise.
SEE ALSO
fann_train_on_data(3), fann_cascadetrain_on_file(3).
PHP Documentation Group FANN_CASCADETRAIN_ON_DATA(3)