SUMMARY.md

Summary

• Deep Cognition Platform Introduction
• Deep Learning Basics
  • What's machine learning?
  • What's deep learning?
  • Basic introduction 1
  • Basic introduction 2
  • Convolutional neural networks (CNN)
  • Recurrent neural networks (RNN) and LSTM 1
  • Recurrent neural networks (RNN) and LSTM 2
• Get Started
  • MNIST example walkthrough
    • Step-1: Create a Project
    • Step-2: Upload data
    • Step-3: Specify pre-processing options
    • Step-4: Create a model
    • Step-5: Train and evaluate
    • Step-6: Download and deploy
• Platform Reference
  • DL Studio Capabilities
  • Projects
  • Project
    • Data Tab
    • Model Tab
    • Hyperparameter Tab
    • Training Tab
    • Results Tab
    • Inference Tab
  • Datasets
  • File Browser
  • Notebook
  • Usage
  • Accounts
• Examples
  • CNN
    • MNIST handwritter digits recognition
    • Image Classification on CIFAR-10 dataset
  • Text Classification
    • Reuters Newswire Topics Classification
    • Sentiment Prediction on IMDB Movie Review Text
• How To
  • Datasets
    • Upload your own dataset
    • Encode multi-dimensional data as numpy file
  • Modeling
    • Finetune an existing model
    • Restore older model
  • Training
    • Compare two runs
    • Make cross validation model
  • Deploy
    • Download and use trained model
• Frequently asked questions (FAQ)