This project was completed as a part of the Honors portion of the Neural Networks and Deep Learning Course on Coursera.
Credit to DeepLearning.AI and the Coursera platform for providing the course materials and guidance.
In this report, I have successfully built a cat/not-a-cat classifier by leveraging functions from a previous assignment to construct a deep network. The primary aim was to achieve an improved level of accuracy compared to the earlier logistic regression implementation.
Through this project, I have acquired crucial skills, including the ability to build and train a deep L-layer neural network, thus enabling me to tackle more complex supervised learning tasks. Additionally, I have applied this neural network to the specific task of classifying cat images from non-cat images.
