Book Image

Java Deep Learning Projects

Book Image

Java Deep Learning Projects

Overview of this book

Java is one of the most widely used programming languages. With the rise of deep learning, it has become a popular choice of tool among data scientists and machine learning experts. Java Deep Learning Projects starts with an overview of deep learning concepts and then delves into advanced projects. You will see how to build several projects using different deep neural network architectures such as multilayer perceptrons, Deep Belief Networks, CNN, LSTM, and Factorization Machines. You will get acquainted with popular deep and machine learning libraries for Java such as Deeplearning4j, Spark ML, and RankSys and you’ll be able to use their features to build and deploy projects on distributed computing environments. You will then explore advanced domains such as transfer learning and deep reinforcement learning using the Java ecosystem, covering various real-world domains such as healthcare, NLP, image classification, and multimedia analytics with an easy-to-follow approach. Expert reviews and tips will follow every project to give you insights and hacks. By the end of this book, you will have stepped up your expertise when it comes to deep learning in Java, taking it beyond theory and be able to build your own advanced deep learning systems.
Table of Contents (13 chapters)

Answers to questions

Answer to question 1: We can train a YOLO network from scratch, but that would take a lot of work (and costly GPU hours). As engineers and data scientists, we want to leverage as many prebuilt libraries and machine learning models as we can, so we are going to use a pre-trained YOLO model to get our application into production faster and more cheaply.

Answer to question 2: Perhaps yes, but the latest DL4J release provides only YOLO v2. However, when I talked to their Gitter (see https://deeplearning4j.org/), they informed me that with some additional effort, you can make it work. I mean you can import YOLO v3 with Keras import. Unfortunately, I tried but could not make it workfullly.

Answer to question 3: You should be able to directly feed your own video. However, if it does not work, or throws any unwanted exception, then video properties such as frame rate...