This repository is part of my deep learning learning journey inspired by the Coursera Deep Learning Specialization. It focuses on deep learning fundamentals and practical implementations.

The repository is organized into the following directories:

• Project: Python_Basics_With_Numpy.ipynb
• Description: A brief introduction to Python and Numpy.

• Project: Logistic_Regression_with_a_Neural_Network_mindset.ipynb
• Description: Building a logistic regression classifier to recognize cats.

• Project: Planar_data_classification_with_onehidden_layer.ipynb
• Description: Implementation of a simple neural network with a hidden layer for planar data classification.

• Project: Building_your_Deep_Neural_Network_Step_by_Step.ipynb
• Description: Implementation of all the functions required to build a deep neural network step by step.

• Project: Deep_Neural_Network_Application.ipynb
• Description: Implementation of a deep network and its application to cat vs non-cat image classification.

This repository is part of my deep learning journey inspired by the Coursera Deep Learning Specialization.

This repository is yet to be complete but will be updated with more projects and learning materials.