-
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
-
Topic modeling with Latent Dirichlet Allocation
- Decomposing text documents with LDA
- LDA with scikit-learn
-
Summary
Please refer to the README.md file in ../ch01 for more information about running the code examples.