The following tutorials are geared to help you get more out of the SignalPop AI Designer.
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- Create and Train a GPT model to learn Shakespeare
- Create a Sequence-to-Sequence Chat-bot
- 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