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Java Deep Learning Solutions

Video Description

Understand Deep Learning algorithms with the most famous Java Framework: DL4J

About This Video

  • A comprehensive guide to understanding Deep Learning using Java
  • Covers the implementation of Deep Learning with DeepLearning4j using the latest techniques and examples
  • Shows how to solve the most common Deep Learning problems.

In Detail

Deep Learning is part of a broader family of machine learning methods based on learning data representations. Deeplearning4j is a Deep Learning programming library written in Java and the Java Virtual Machine (JVM) and is a computing framework with wide support for Deep Learning algorithms.

In this course, you start by installing Deep Learning software for Java. You learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. The course will take you into Neural Networks, working with Perceptron, XOR, and Gradient Descent on code examples. It then covers Convolutional Networks with extraction, Max pooling, and Softmax. You'll get hands-on with working examples at the end of each section. It also covers Recurrent Neural Network, explaining all the features of its Architecture. Finally, you'll learn about Word2Vec's different models and how to work with them via practical examples.

By the end of this video course, you’ll be ready to tackle Deep Learning with Java.

All the code and supporting files for this course are available on Github at - https://github.com/PacktPublishing/Java-Deep-Learning-Solutions-