07-19-2007
I had no formal UNIX training nor did I have a University education. I was always technically minded and installed Linux (a very early SUSE release) on a home system to play around with. I purchased a couple of UNIX books, and taught myself Linux and Solaris. Got my first break as a Junior admin by demonstrating my self-taught skills and knowledge at interview, and then just learnt on the job as well as building up a huge (O'Reilly) bookshelf and learning at home. I am now a Senior UNIX/Linux System Administrator looking after hundreds of Solaris and Linux systems for one of Australia's largest DNS/Web Hosting/Mail companies.
I suppose my points are:
* You can make anything you want out of your career if you're willing to work for it.
* You don't need formal training. If you have a passion for the field, and aren't just learning it to "get the job", you'll pick it up. UNIX is a hobby for me, not just a profession.
* It won't happen over night. I have years of experience under my belt, but never stop learning more. There'll always be someone who knows (much) more than you - learn from them - don't feel intimidated.
Just my 2 cents....
Cheers,
ZB
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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)