Dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with Java
About This Book
- Go beyond the theory and put Deep Learning into practice with Java
- Find out how to build a range of Deep Learning algorithms using a range of leading frameworks including DL4J, Theano and Caffe
- Whether you're a data scientist or Java developer, dive in and find out how to tackle Deep Learning
Who This Book Is For
This book is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It would also be good for machine learning users who intend to leverage deep learning in their projects, working within a big data environment.
What You Will Learn
- Get a practical deep dive into machine learning and deep learning algorithms
- Implement machine learning algorithms related to deep learning
- Explore neural networks using some of the most popular Deep Learning frameworks
- Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms
- Discover more deep learning algorithms with Dropout and Convolutional Neural Networks
- Gain an insight into the deep learning library DL4J and its practical uses
- Get to know device strategies to use deep learning algorithms and libraries in the real world
- Explore deep learning further with Theano and Caffe
In Detail
AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It'lcĄ