Introduction
Deep learning is simply neural networks with multiple layers. It is also known as deep neural network learning or unsupervised feature learning. The author believes that deep learning will become the next accomplice of machine learning practitioners and data scientists because of its ability to solve real-world data problems.
Deep Learning for Java (DL4j) is an open-source, distributed Java library for deep learning for JVM. It comes with other libraries, as follows:
Deeplearning4J: Neural Net Platform
ND4J: NumPy for the JVM
DataVec: Tool for machine learning ETL operations
JavaCPP: The bridge between Java and native C++
Arbiter: Evaluation tool for machine learning algorithms
RL4J: Deep reinforcement learning for the JVM
However, we will be focusing on a few key recipes for DL4j only, given the scope of this book. To be specific, we will be discussing recipes to use Word2vec algorithm and their use for real-world NLP and information retrieval problem, deep belief neural networks...