DeepLearning4J for Image Recognition Training Course

Getting Started

• Quickstart: Running Examples and DL4J in Your Projects
• Comprehensive Setup Guide

Convolutional Neural Networks

• Convolutional Net Introduction
• Images Are 4-D Tensors?
• ConvNet Definition
• How Convolutional Nets Work
• Maxpooling/Downsampling
• DL4J Code Sample
• Other Resources

Datasets

• Datasets and Machine Learning
• Custom Datasets
• CSV Data Uploads

Scaleout

• Iterative Reduce Defined
• Multiprocessor / Clustering
• Running Worker Nodes

Advanced DL2J

• Build Locally From Master
• Use the Maven Build Tool
• Vectorize Data With Canova
• Build a Data Pipeline
• Run Benchmarks
• Configure DL4J in Ivy, Gradle, SBT etc
• Find a DL4J Class or Method
• Save and Load Models
• Interpret Neural Net Output
• Visualize Data with t-SNE
• Swap CPUs for GPUs
• Customize an Image Pipeline
• Perform Regression With Neural Nets
• Troubleshoot Training & Select Network Hyperparameters
• Visualize, Monitor and Debug Network Learning
• Speed Up Spark With Native Binaries
• Build a Recommendation Engine With DL4J
• Use Recurrent Networks in DL4J
• Build Complex Network Architectures with Computation Graph
• Train Networks using Early Stopping
• Download Snapshots With Maven
• Customize a Loss Function