Programming Artificial Intelligence Utilities is a package that aims to make artificial intelligence and machine learning programming easier through abstractions of extensive APIs, research paper implementations, and data manipulation.
Package Features
- Analytics
- Plotting of data through embedding algorithms, such as Isomap and TSNE
- Audio
- Recording and playing
- Volume, speed, and pitch manipulation
- Trimming and Splitting
- Spectrogram, Fbanks, and MFCC creation
- Audio file conversions
- Image
- Simplified OpenCV Interface
- Autoencoder
- Trainer and Predictor
- Trainer with extra decoder
- VAE Trainer
- Evolution Algorithm
- One dimensional evolution algorithm
- Hyperparameter tuner
- GAN
- GAN Trainer
- GANI Trainer (GAN which takes provided Inputs)
- Cycle GAN Trainer
- Predictors
- Neural Network
- Trainer and Predictor
- Dense layers that combine batch norm
- Convolution layers that combine batch norm, max pooling, upsampling, and transposing
- Reinforcement
- OpenAI Gym wrapper
- Multi-agent adverserial environment
- Greedy, ascetic, and stochastic policies
- Noise policies
- Exponential, linear, and constant decay
- Normal memory and efficient time distributed memory (for stacked states)
- Agents
- QAgent: Q-learning with a table
- DQNAgent Q-learning with a neural network model
- PGAgent: State to action neural network model (Actor) trained with policy gradients
- DDPGAgent: State to continous action space neural network model trained with deterministic policy gradients
- Reinforcement Agents
- DQNPGAgent: Combination of a DQN and PG agent into one agent
- A2CAgent: Advantage Actor Critic agent
- PPOAgent: Proximal Policy Optimization agent
- TD3Agent: Twin Delayed DDPG Agent
- PGCAgent: Continuous variant of PGAgent
- A2CCAgent: Continuous variant of A2CAgent