/intro-to-ai

Introduction to AI

Primary LanguageJupyter Notebook

Introduction to Artificial Intelligence

Neurons (Theory)

  • Real-life decission making process
  • Neuron
  • Step activation function
  • Universality of neurons

Tensors

  • Basics
  • Storage

Learning

  • Temperature conversion
  • Learning problem
  • Loss function
  • Calculas (aka backpropagation)
  • Learning the weights & biases

MNIST & FMNIST

  • ReLU activation functions
  • Softmax function
  • Multi-layered neural nets
  • Neural Networks module

Neural Networks

  • Backpropagation
  • Optimizer function
  • Cross-entropy cost function
  • Overfitting & Regularization
  • Weight Initilization
  • Hyperparameters
  • Gradient Descent & its Descendents

CNNs

LSTMs

GANs

References