Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge.

Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. You will learn how to use Java machine learning libraries and apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, you will learn the techniques and tools you need to quickly gain insight from complex data. You will apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text Later you will focus on what Perceptrons are and their features. You will implement self-organizing maps using practical examples. Further on, you will work with the examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. Finally, you will learn methods to optimize and adapt neural networks in real time. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work.