Week 4 – Deep Learning & Neural Networks

This week focused on deep learning and neural networks, which are more advanced forms of machine learning. I learned that neural networks are inspired by the human brain and use layers of “neurons” to process information. Concepts like activation functions (ReLU, sigmoid, softmax) showed me how models decide what information matters. It was interesting to see how these systems can handle complex tasks like image recognition and speech processing. In Google Colab, I followed along with building a neural network to classify handwritten digits. Even though the code looked complex at first, breaking it down step-by-step made it manageable. When I saw the model reach around 97% accuracy, it really clicked for me how powerful these systems are. This made me think about real-world uses like facial recognition or automated systems in business. This week showed me how deep learning goes beyond basic predictions and can handle more complex data like images and language. As someone interested in marketing, I can see how this could be used for customer insights, product recommendations, and even content personalization. It made AI feel a lot more relevant to my career.

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