Binary Classification with Keras: Build Your First Neural Network

Deep learning can seem intimidating, but building your first classifier is straightforward when you understand the fundamental architecture. This text-based course guides you step-by-step through the process of converting regression-style networks into powerful binary classifiers. You will learn how to structure data, configure layers, and select the right activation functions to separate data into two distinct categories. By the end of this course, you will confidently design, compile, and evaluate your own binary classification models in Keras. What you will learn: Understand foundational neural network concepts, including weights, biases, and activation functions; Configure Keras layers specifically for binary classification using the sigmoid activation function; Apply binary cross-entropy loss and select appropriate optimizers for training; Prepare and split your datasets using modern data-handling libraries; Evaluate model performance using metrics like accuracy, precision, and recall. This course begins with essential terminology and the core mechanics of neural networks before moving into step-by-step construction and model evaluation. It is designed for beginners who have a basic understanding of Python and want to enter the world of deep learning. Start building your first classification model today.