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Python: deeper insights into machine learning: leverage benefits of machine learning techniques using Python: a course in three modules


Book Informaton

Python: deeper insights into machine learning: leverage benefits of machine learning techniques using Python: a course in three modules

Author

Raschka, Sebastian; Julian, David; Hearty, John

Series

Learning path

Year of Publication

2016

Publisher

Packt Publishing

Pages

916

Language

en

ISBN

9781787128576, 1787128571, 9781787128545, 1787128547

ARI Id

1673283392874


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Showing 1 to 20 of 139 entries
Chapters/HeadingsAuthor(s)PagesInfo
Giving Computers the Ability to Learn from Data
The three different types of machine learning
An introduction to the basic terminology and notations
A roadmap for building machine learning systems
Using Python for machine learning
Summary
Training 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
Choosing a classification algorithm
First steps with scikit-learn
Modeling class probabilities via logistic regression
Maximum margin classification with support vector machines
Solving nonlinear problems using a kernel SVM
Decision tree learning
K-nearest neighbors – a lazy learning algorithm
Dealing with missing data
Handling categorical data
Partitioning a dataset in training and test sets
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 139 entries