Re:Tensorflow.js – A Practical Guide
by galfarragem on Wednesday June 13, 2018 @01:01PM
(#17304918)
If I understand it correctly:
- Tensorflow is the best tool to make the grunt work necessary to calibrate the parameters of fitting algorithms.
- Models of fitting algorithms are human proposed and where the ML 'art' is. Seems to be kind of reverse engineering.
Accurate, although in most cases, the art is not in choosing the algorithm (often a regular feed-forward, covolutional or recurrent neural network) but the hyperparameters (regularization, number of layers, units, etc.) and sometimes the way the data is fed (augment the dataset with distortions? sample negative examples randomly? etc.)
For example, x can be tens of thousands of images of cats and dogs, and y can be 1 for a dog and 0 for a cat. The goal for the fitting algorithm is to find parameters that describe the concept of a cat and a dog so that it can can generalize and categorize general images of cats and dogs. A bad fit would be if the network just memorized the example images.