Deeplearning4j Documentation
Posted by Armando Brito Mendes | Filed under materiais para profissionais, software
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O site de um pacote java para deeplearing com montes de info. sobre redes neuronais e afins.
- How To
- Quickstart: Running Examples and DL4J in Your Projects
- Comprehensive Setup Guide
- Build Locally From Master
- Contribute to DL4J (Developer Guide)
- Choose a Neural Net
- 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
- Introduction to Neural Networks
- Multilayer Neural Nets
- Tutorials
- Datasets
- Scaleout
- Text
- Resources
- DL4J, Torch7, Theano and Caffe
- Glossary of Terms for Deep Learning and Neural Nets
- Deep Learning’s Accuracy
- DataVec: ETL for ML
- ND4J Backends: How They Work
- Model Zoo
- Unsupervised Learning: Use Cases
- Eigenvectors, PCA, Covariance and Entropy
- Thought Vectors, AI and NLP
- Questions to Ask When Applying DL
- AI, Machine Learning and Deep Learning
- DL and Reinforcement Learning
- Javadoc: DL4J Methods and Classes
- Canova Javadoc: Canova Methods and Classes
- ND4J User Guide
- ND4J Javadoc
- Scala, Spark and Deep Learning
- Further Reading on Deep Learning
- Deep Learning in Other Languages
- Use Cases
- Architecture
- Features
- Roadmap
- About
- Open Data
- Latest Release Notes
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Tags: análise de dados, big data, data mining, desnvolvimento de software, machine learning
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