See what happens after the prompt—and build the technical knowledge to work with LLMs more effectively. This laser-focused four-chapter ebook combines clear explanations with hands-on implementation, helping you connect foundational concepts to transformer architecture, GPT construction, and modern text-generation techniques. With this practical primer, you’ll strengthen your understanding, sharpen your technical judgment, and approach text-generating models with greater confidence.
What are Generative Adversarial Networks (GANs); learn how to play with them by modifying a GAN implementation for new tasks and losses.
Inside Deep Learning illuminates the inner workings of deep learning algorithms in a way that even machine learning novices can understand. You’ll explore deep learning concepts and tools through plain language explanations, annotated code, and dozens of instantly useful PyTorch examples. Each type of neural network is clearly presented without complex math, and every solution in this book can run using readily available GPU hardware!