In this section, we will be developing a video object classification application using pre-trained YOLO models (that is, transfer learning), DL4J, and OpenCV that can detect labels such as cars, and trees inside the video frame. To be frank, this application is also about extending an image detection problem to video detection. So let's get started.
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Book Overview & Buying
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Table Of Contents
Java Deep Learning Projects
By :
Java Deep Learning Projects
By:
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)
Preface
Free Chapter
Getting Started with Deep Learning
Cancer Types Prediction Using Recurrent Type Networks
Multi-Label Image Classification Using Convolutional Neural Networks
Sentiment Analysis Using Word2Vec and LSTM Network
Transfer Learning for Image Classification
Real-Time Object Detection using YOLO, JavaCV, and DL4J
Stock Price Prediction Using LSTM Network
Distributed Deep Learning – Video Classification Using Convolutional LSTM Networks
Playing GridWorld Game Using Deep Reinforcement Learning
Developing Movie Recommendation Systems Using Factorization Machines
Discussion, Current Trends, and Outlook
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