- Artificial neurons – a brief glimpse into the early history of machine learning
- The formal definition of an artificial neuron
- The perceptron learning rule
- Implementing a perceptron learning algorithm in Python
- An object-oriented perceptron API
- Training a perceptron model on the Iris dataset
- Adaptive linear neurons and the convergence of learning
- Minimizing cost functions with gradient descent
- Implementing an Adaptive Linear Neuron in Python
- Improving gradient descent through feature scaling
- Large scale machine learning and stochastic gradient descent
- Summary
Please refer to the README.md file in ../ch01 for more information about running the code examples.