Deep Learning Essentials: From Neural Nets to Applications
Deep Learning Essentials: From Neural Nets to Applications Deep learning helps computers learn from data. It uses many small steps, called layers, to transform raw information into useful decisions. This approach works well in image, text, sound, and more, and it often matches or exceeds traditional methods. The ideas are simple at heart, but they unite many tools for real problems. At the core are neural networks. A network has layers of neurons, each with weights that get adjusted during training. When you pass data through the network, signals are amplified or dampened by activation functions. The model learns by comparing its output to the correct answer and updating weights with backpropagation and gradient descent. With enough data and practice, a small model can solve surprisingly difficult tasks. ...