Learn to Build a Multilayer Perceptron with Real-Life Examples and Python Code

This tutorial guides readers through building perceptrons and multi-layer perceptrons (MLPs) using custom code, scikit-learn, and Keras. It covers single and multi-layer architectures, explaining key concepts and implementing binary classifiers for fraud detection. The guide demonstrates data preprocessing, model training, and evaluation, comparing different optimizers and approaches. It provides insights on when to use scikit-learn's MLPClassifier versus Keras, offering a practical introduction to neural network fundamentals and implementation.