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1. Giving Computers the Ability to Learn from Data

Giving Computers the Ability to Learn from Data

Building intelligent machines to transform data into knowledge

The three different types of machine learning

Introduction to the basic terminology and notations

2. Training Simple Machine Learning Algorithms for Classification

Training Simple Machine Learning Algorithms for Classification

Artificial neurons – a brief glimpse into the early history of machine learning

Implementing a perceptron learning algorithm in Python

Adaptive linear neurons and the convergence of learning

5. Compressing Data via Dimensionality Reduction

Compressing Data via Dimensionality Reduction

7. Combining Different Models for Ensemble Learning

Combining Different Models for Ensemble Learning

Learning with ensembles

Combining classifiers via majority vote

Bagging – building an ensemble of classifiers from bootstrap samples

Leveraging weak learners via adaptive boosting

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Release date 2022-03-15
Latest update 2022-11-15
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