We'll start by describing what machine learning is, and introduce a simple learning algorithm: linear regression + gradient descent. Using this algorithm, we'll introduce the core concepts in machine learning: model parameters, cost function, optimization method, and overfitting and regularization. This section ends with a visual review of these concepts and a note on some of the folk wisdom that people have learnt over the years.
- An introduction to Machine Learning
- Algorithms for Supervised Learning
- Neural Networks and Deep Learning
- Algorithms for Unsupervised Learning
- Ensemble methods, and methods for small datasets
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