Core ML

Classical ML, deep learning, training patterns, and foundations

Deep Learning Foundations

Core ML
Backpropagation
The algorithm that tells each weight in a network how to nudge itself so the next prediction comes out a little less wrong.
Core ML
Neural Networks (Multi-Layer Perceptron)
A stack of simple math units that learns to turn raw inputs into useful predictions by bending straight lines into curves.

Convolutional Neural Networks

Core ML
Convolutional Neural Networks
Neural networks that scan an image with small pattern-detectors, so they recognize a cat whether it sits in the corner or the center.

Optimization

Core ML
Gradient Descent
How a model learns by feeling which way is downhill on an error landscape and taking small steps in that direction until it can't improve.

Regularization

Core ML
Regularization
A set of gentle brakes that stop a model from memorizing its training data, so it learns the real pattern and still works on data it has never seen.