paiutils 4.0.0

An artificial intelligence utilities package built to remove the delays of machine learning research.

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