Deep Learning with Java: A Complete Guide

Course details

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Getting Started with Java Deep Learning, shows you how to install the environment, where Git is used as version control, Eclipse or IntelliJ as an IDE, and mostly Gradle with a little bit of Maven as a build tool. Learn how to use the DL4J and apply deep learning to a range of real-world use cases. You will then be introduced to Neural networks and later you will learn how to implement them. You will also be given an insight about various deep learning algorithms. Lastly, be trained to tune Apache Spark.
The second course, Java Deep Learning Solutions, shows you 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. It also covers Recurrent Neural Network, explaining all the features of its Architecture. Finally, learn about Word2Vec's different models and how to work with them via practical examples.
By the end of this Learning Path, youll be ready to tackle Deep Learning with Java.

About the Author
Sercan Karaoglu gained his BSc in Mathematics Engineering at Istanbul Technical University. Karaoglu also completed a Research and Development project at age 23, at Foreks, in collaboration with The Scientific and Technological Research Council of Turkey(TUBITAK). This project was related to the application of Artificial Neural Networks in Financial Trading Decision Support Systems and Market Simulation for Intraday and Daily Trading. Currently, he develops High Throughput-Low Latency Reactive Microservices and Reactive Stream applications at work and researches the topics of Deep Learning and Machine Learning. He is Java Software Engineer at the Dissemination Department of Foreks Information Systems, which is one of the leading IT companies in Turkeys financial sector. It has specialized in software that is directly integrated with financial professionals and Istanbul Stock Market for over 26 years. He is currently studying for his MSc in Computer Engineering at Bahcesehir University in the field of Big Data Analytics and Management.
Shreenidhi Sudhakar is a Deep Learning enthusiast. He has completed his Masters from Florida Institute of Technology with specialization in Machine Learning. On the work front, he has around 3 years of experience in IT as a Principal Deep Learning Intern and Full Stack Java Developer. He also writes articles on Deep Learning for the blog Towards Data Science.