Tutorials

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

• • Create and Train a Liquid Neural Net to follow a Sine curve.
  • Create and Train a Temporal Fusion Transformer Model to predict retail demand flows.
  • Create and Train a Temporal Fusion Transformer Model to predict electricity use.
  • Create and Train a Temporal Fusion Transformer Model to predict traffic flows.
  • Create and Train a ChatGPT like model to Translate English to French.
  • Create and Train a GPT model to learn Shakespeare.
  • 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.