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

• Neural Networks & Deep Learning: http://neuralnetworksanddeeplearning.com/index.html
• Deep Learning with PyTorch: https://pytorch.org/deep-learning-with-pytorch
• PyTorch with Examples: https://pytorch.org/tutorials/beginner/pytorch_with_examples.html
• PyTorch Tutorials: https://pytorch.org/tutorials/index.html