Dive into the world of neural networks with this comprehensive 1-hour 16-minute talk from the Data Science Festival Summer School 2021. Explore the fundamental components of neural networks, including nodes, layers, activation functions, loss functions, and optimizers. Gain insights into neural network architecture and follow along with a Python example for movie review classification. Discover advanced concepts like Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNNs), learning about their building blocks such as convolutional operations, padding, pooling, and border effects. Apply your newfound knowledge to a real-life image classification problem, distinguishing between cats and dogs. Led by Timothy Flack and Annelies Gerber, Data Scientists at Royal Mail, this session provides a solid foundation for understanding and implementing neural networks in various applications.