Building Deep Neural Networks using Deep Learning for Java(DL4J)
summary
Hands-on walkthrough of DL4J with concrete results: shows installation via JDK and Maven, runs examples from the GitHub repo inside IntelliJ, and demos a classifier that reports 96% accuracy with confusion counts (17 and 20 mislabels). Presents the DL4J UI for layer activations and loss monitoring, demonstrates GPU speedup 1.5 days → 40 minutes for CNN training, and trains a Word2Vec on Shakespeare to inspect cosine-nearest words. Tools used: DL4J, IntelliJ, Maven, GPUs; examples build and run locally.
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chapters (11)
- 0:00Introduction
- 4:00Outline
- 6:50Machine Learning
- 11:40Deep Neural Networks
- 18:25Machine Learning Process
- 22:30Defining the Problem
- 28:10Real Life Applications
- 35:50Deep Learning frameworks
- 38:22Installation
- 40:30Examples
- 46:35Words Awake
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