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The objective of this notebook is to apply **Logistic Regression** for solving a binary classification task. The goal is to develop a clear understanding of the model workflow, implementation using scikit-learn, and model evaluation techniques.
A collection of TensorFlow/Keras notebooks demonstrating custom model subclassing and custom layer creation. Includes regression on California Housing and filtered MNIST classification, showcasing preprocessing, training, evaluation, and deep learning customization skills.
(Coursera/Course4/Week1/Project1) -- SE Fundamentals with Duke University / Principles of Software Design / Earthquakes: Programming and Interfaces / Searching Earthquake Data