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It concludes with exploring autoencoders and generative models such as Hopfield Networks and Boltzmann Machines, applying these techniques to a diverse set of practical applications. These applications include image classification, object detection, sentiment analysis, COVID-19 detection, and ChatGPT.         By the end of this book, you will have gained a thorough understanding of deep learning, from its fundamental principles to its innovative applications, enabling you to apply this knowledge to solve a wide range of real-world problems.         What You Will Learn      What are deep neural networks? What is transfer learning, multi-task learning, and end-to-end learning? What are hyperparameters, bias, variance, and data division? 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