Tutorials

The following tutorials are geared to help you get more out of the SignalPop AI Designer.

• • Debug complex AI Solutions
  • Detect objects from images using Single-Shot Multi-Box Detection (SSD)
  • Detect object in a video using Single-Shot Multi-Box Detection (SSD)
  • Create a Triplet Net to learn MNIST using only 1% of the images.
  • Create a Siamese Net to learn MNIST
  • Create a Neural Style Transfer
  • Create and Train a Sigmoid based Policy Gradient RL Model on Cart-Pole
  • Create and Train a Softmax based Policy Gradient RL Model on Cart-Pole
  • Create and Train a Sigmoid based Policy Gradient RL Model on ATARI Pong
  • Create and Train a Noisy-Net based Deep Q-Learning RL Model on ATARI Breakout
  • Create and Train an LSTM based Recurrent Model on Shakespeare
  • Create and Train an LSTM_SIMPLE based Recurrent Model on Shakespeare
  • Create and Train a Domain-Adversarial Neural Network
  • Create and Train the ResNet-56 on Cifar-10
  • Create and Train a Deep Convolution Auto-Encoder with Pooling on MNIST