Duration
14 hours (usually 2 days including breaks)
Requirements
Knowledge of Deep Learning, and one of the following languages:
- Java
- Scala
and the following software:
- Java (developer version) 1.7 or later (Only 64-Bit versions supported)
- Apache Maven
- IntelliJ IDEA or Eclipse
- Git
Overview
Deeplearning4j is an open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Spark, DL4J is designed to be used in business environments on distributed GPUs and CPUs.
Word2Vec is a method of computing vector representations of words introduced by a team of researchers at Google led by Tomas Mikolov.
Audience
This course is directed at researchers, engineers and developers seeking to utilize Deeplearning4J to construct Word2Vec models.
Course Outline
Getting Started
- DL4J Examples in a Few Easy Steps
- Using DL4J In Your Own Projects: Configuring the POM.xml File
Word2Vec
- Introduction
- Neural Word Embeddings
- Amusing Word2vec Results
- the Code
- Anatomy of Word2Vec
- Setup, Load and Train
- A Code Example
- Troubleshooting & Tuning Word2Vec
- Word2vec Use Cases
- Foreign Languages
- GloVe (Global Vectors) & Doc2Vec