Plan du cours

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

 

Pré requis

  • Java
  21 heures

Nombre de participants



Prix par participant

Nos Clients témoignent (4)

Cours Similaires

Deep Learning AI Techniques for Executives, Developers and Managers

  21 heures

Deep Learning for Finance (with R)

  28 heures

Deep Learning for Banking (with R)

  28 heures

Catégories Similaires