Deep Learning with Java

• Extract features from unstructured data using ND4J
• Use DL4J to perform fast and efficient deep learning training
• Perform automatic speech recognition with DL
• Use RNN with DL to achieve more precise results based on previous history
• Process image data using multiple layers with DL4J
• Use Word2Vect to perform feature extraction on text data
• Predict using classification with a multilayered approach

This step-by-step, practical tutorial teaches you how to implement key concepts and adopts a hands-on approach to key algorithms to help you develop a greater understanding of deep learning. You will learn how to use the DL4J library and apply deep learning to a range of real-world use cases. This course will also help you solve challenging problems in image processing, speech recognition, and natural language modeling; it will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights.

By the end of this course, you’ll be ready to tackle deep learning with Java. Whether you come from a data science background or are a Java developer, you will become part of the deep learning revolution!

The code bundle for this course is available at https://github.com/PacktPublishing/Deep-Learning-with-Java

• Learn key algorithms needed to enhance your understanding of deep learning
• Use Java and deep neural networks to solve problems with the help of image processing, speech recognition, and natural language modeling
• Use the DL4J library and apply deep learning concepts to real-world use cases