Artificial Intelligence (AI) Patterns, Neurons and Neural Networks

 

 

Artificial Intelligence (AI) Patterns, Neurons and Neural Networks

This resource catalog is published by Arcitura Education in support of the AI Specialist Certification program. This content was developed for official Artificial Intelligence courses. (Note that this site is still undergoing improvements. Please provide feedback or report issues to info@arcitura.com).

To learn more about the Arcitura AI Specialist Certification program, visit: https://www.arcitura.com/ai

    • Data Wrangling Patterns
      • Feature Encoding
      • Feature Imputation
      • Feature Scaling
      • Feature Encoding
      • Dimensionality Reduction
    • Supervised Learning Patterns
      • Supervised Network Configuration
      • Image Recognition
      • Sequence Identification
    • Unsupervised Learning Patterns
      • Pattern Identification
      • Content Filtering
    • Model Evaluation Patterns
      • Training Performance Evaluation
      • Prediction Performance Evaluation
      • Baseline Modeling
    • Model Optimization Patterns
      • Overfitting Avoidance
      • Frequent Model Retraining
      • Transfer Learning
    • Fundamental Neural Network Architectures
      • Perceptron (P)
      • Feedforward (FF)
      • Radial Basis Forward (RBF)
      • Deep Feedforward (DFF)
    • Architectures with Encoding and Decoding Layers
      • AutoEncoder (AE)
      • Sparse AutoEncoder (SAE)
      • Variational AutoEncoder (VAE)
      • Denoising AutoEncoder (DAE)
    • Recurrent Cell-based Architectures
      • Recurrent Neural Networks (RNNs)
      • Echo State Network (ESN)
    • Memory-Influenced Architectures
      • Long/Short Term Memory (LSTM)
      • Neural Turing Machine (NTM)
    • Parabolicity Cell-Driven Architectures
      • Boltzmann Machine (BM)
      • Restricted Boltzmann Machine (RBM)
      • Deep Belief Network (DBN)
      • Markov Chain (MC)
    • Pool and Kernel Influenced Architectures
      • Deep Convolutional Network (DCN)
      • Deconvolutional Network (DN)
      • Deep Convolutional Inverse Graphics Network (DCIGN)
    • Hidden Cell Connection Architectures
      • Extreme Learning Machine (ELM)
      • Deep Residual Network (DRN)
      • Support Machine Vector (SVM)
      • Kohonen Network (KN)
    • Other Neural Network Architectures
      • Hopfield Network
      • Generative Adversarial Network (GAN)
      • Liquid State Machine (LSM)
    • Neuron Cell Types
      • Backfed Input Neuron
      • Convolution Kernel/Pool Neuron
      • Different Memory Neuron
      • Hidden Neuron
      • Input Neuron
      • Kernel Neuron
      • Match Input/Output Neuron
      • Memory Neuron
      • Noisy Input Neuron
      • Output Neuron
      • Probabilistic Hidden Neuron
      • Recurrent Memory Neuron
      • Recurrent Neuron
      • Spiking Hidden Neuron