Designed a neural network with multi-class regression to recognize handwritten digits (0-9) and to represent complex models that form non-linear hypothesis. We implement a feedforward propagation for the neural network and use the weights from our previous repository https://github.com/madison-freeman/logistic-regression-model.
Designed a neural network with multi-class regression to recognize handwritten digits (0-9) and to represent complex models that form non-linear hypothesis. We implement a feedforward propagation for the neural network and use the weights from our previous repository https://github.com/madison-freeman/logistic-regression-model.
BSD 2-Clause "Simplified" License