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