Getting Started

• Deeplearning4j Overview

• Quickstart: Get Started With Deep Learning

• Comprehensive Setup Guide

• Quick Reference: Layers & Functionality

• Build Locally From Master

• Use the Maven Build Tool

• Configure DL4J in Ivy, Gradle, SBT etc.

• Swap CPUs for GPUs

• Overview of the DL4J Ecosystem

• Tour of DL4J Examples

• Deep Learning Benchmarks

Tutorials

• Deep Learning Tutorial Index

• Notebook-Based Tutorials

• MNIST for Beginners

• Using Recurrent Nets in DL4J

• Import Models from Keras to DL4J

• Scientific Computing for Java and the JVM

• DataVec: Vectorization and Preprocessing for Machine Learning

• Neural Net Updaters: SGD, Adam, Adagrad, Adadelta, RMSProp

• Build a Recommendation Engine With DL4J

GET STARTED WITH DEEP LEARNING

Introduction to Deep Learning

• Introduction to Neural Networks

• Questions to Ask When Applying DL

• Deep Learning for Beginners

• Use Cases

• Deep Learning's Accuracy

• Defining AI, Machine Learning and Deep Learning

• Data You Need For Deep Learning

• Multilayer Neural Networks

• Choosing a Neural Network

Neural Networks

• Long Short-Term Memory Units (LSTMs)

• Convolutional Nets for Image Processing

• Recurrent Nets

• Word2Vec: Neural Word Embeddings

• Restricted Boltzmann Machines

• Deep AutoEncoder

• Denoising Autoencoders

• Stacked Denoising Autoencoders

• Generative Adversarial Networks (GANs)

• Deep Reinforcement Learning

• Deep Learning & Symbolic Reasoning

• Backpropagation

Data, Data Pipelines & ETL

• Datasets and Machine Learning

• Workspaces

• Custom Datasets

• CSV Data Uploads

• Open Data

• DataVec: Vectorization ETL for Machine Learning

• Build a Data Pipeline

• Customize an Image Pipeline

• DataVec Javadoc: DataVec Methods & Classes for ETL

Tuning & Training

• Training Neural Networks with Apache Spark

• Distributed Training: Iterative Reduce Defined

• Visualize, Monitor and Debug Network Learning

• Troubleshoot Training & Select Network Hyperparameters

• Train Networks Using Early Stopping

• Interpret Neural Net Output

Deployment to Production

• Skymind Intelligence Layer: Track Experiments and Serve Models

• Installing and configuring SKIL for single/multi node(s)

• Getting started with SKIL Deployment Client

• Running Deep Learning on Distributed GPUs With Spark

• Model Zoo: Pre-trained Models

• Save and Load Models

• Visualize Data with t-SNE

• Perform Regression With Neural Nets

• Use Recurrent Networks in DL4J

• Build Complex Network Architectures with Computation Graph

• Inference: Machine Learning Model Server

Open-Source Community

• Contribute to DL4J (Developer Guide)

• Architecture

• Features

• Roadmap

• Latest Release Notes

• Javadoc: DL4J Methods and Classes

• Gitter Online Support Chatroom

Natural Language Processing

• DL4J's NLP Framework

• Word2vec for Java and Scala

• Doc2vec for Java and Scala

• Textual Analysis and DL

• Bag of Words

• Sentence and Document Segmentation

• Tokenization

• Vocabulary Cache

ND4J: Numpy for the JVM

• ND4J Backends: Hardware Acceleration on CPUs and GPUs

• ND4J User Guide

• ND4J Javadoc

More Machine Learning Beginner's Guides

• Eigenvectors, PCA, Covariance and Entropy

• Thought Vectors, AI and NLP

• Monte Carlo, Markov Chains and Deep Learning

• Unsupervised Learning: Use Cases

• Generative Adversarial Network

• DL and Reinforcement Learning

• Scala, Spark and Deep Learning

• DL4J, Torch7, Theano, TensorFlow, MxNet, Keras and Caffe

• Glossary of Terms for Deep Learning and Neural Nets

• Graph Data and Deep Learning

• Symbolic Reasoning and Deep Learning

• Free Online Courses, Tutorials and Papers

• Deep Learning in Other Languages

Further Resources

• Machine Learning and Deep Learning Demos

• Machine Learning and Deep Learning Software Links

• Machine Learning and Deep Learning Research Groups and Labs

Other Languages

• 中文

• 日本語

• 한글