Dive into a comprehensive 5-hour tutorial on deep learning, covering fundamental concepts and advanced techniques. Explore the differences between AI, ML, DL, and Data Science, and understand why deep learning is gaining popularity. Learn about perceptrons, forward and backward propagation, weight updates, and the chain rule of derivatives. Tackle challenges like the vanishing gradient problem and explore various activation functions, loss functions, and optimizers. Gain hands-on experience with practical implementations of Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN). Compare black box and white box models to deepen your understanding of deep learning architectures and their applications.