GitHub / ZakirCodeArchitect / Intent-classifiers-on-regression-models

This project compares five optimization algorithms (GD, SGD, Momentum, RMSProp, and Adam) on Univariate Linear Regression and a neural network for Intent Classification with the ATIS dataset. It evaluates convergence speed, stability, and final loss, showing that Adam delivers the best performance across both models.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZakirCodeArchitect%2FIntent-classifiers-on-regression-models

Topics: atis-dataset, intent-classification, jupyter-notebook, keras, keras-neural-networks, matplotlib, numpy, python, regression-models, tenserflow

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