Mastering Deep Learning with Java
Neural-net based models with multiple layers have demonstrated to be efficient compact function approximators that generalize beyond the training data. Research in deep learning is largely done in Python, causing enterprises where Java dominates to lag behind in leveraging state-of-art deep learning models in applications. This book attempts to fill that void.
Mastering Deep Learning with Java brings the utilization of the next-generation capability of deep neural nets and finding patterns in your datasets using powerful deep learning techniques. You will develop the capabilities to develop complex neural network models using Deeplearning4j, one of Java's popular and preferred libraries for deep learning. The book would teach you how you can design optimized neural networks in the areas of computer vision, natural language processing, and computer games.
This book covers the workhorse models of deep learning starting with simple feedforward neural nets, convolution neural nets, sequence models, to the more recently popular attention based models (GPT-2, BERT etc.)
By the end of this book, you will be well equipped to design, develop and deploy efficient, enterprise-grade deep learning models from scratch using Java.
|Date Of Publication||23 Jan 2020|