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Data science from scratch : first principles with Python / Joel Grus
By: Grus, Joel [autor]
.
Contributor(s): Cronin, Michele [editor] | Baker, Deborah [productor editorial] | Head, Rachel [corrector de pruebas] | McConville, Judy [indexador] | Futato, David [diseñador de interior] | Montgomery, Karen [diseñador de cubierta] | Demarest, Rebecca [ilustrador].
Material type: 
TextPublisher: Sebastopol : O'Reilly Media, 2019Edition: Segunda edición.Description: xvii, 384 páginas : figuras ; 24 x 17 cm.ISBN: 9781492041139; 1492041130.Subject(s): Administración de bases de datos | Diseño de bases de datos | Python (lenguaje de programación de computadores) | Procesamiento de datos -- MatemáticasDDC classification: 005.7565 G892d
Contents:
Preface to the Second Edition |
Preface to the First Edition
Introduction |
A crash course in Python |
Visualizing data |
Linear algebra |
Statistics |
Probability |
Hypothesis and inference |
Gradient descent |
Getting data |
Working with data |
Machine learning |
k-Nearest neighbors |
Naive bayes |
Simple linear regression |
Multiple regression |
Logistic regression |
Decision trees |
Neural networks |
Deep learning |
Clustering |
Natural language processing |
Network analysis |
Recommender systems |
Databases and SQL |
MapReduce |
Data ethics |
Go forth and do data science |
Index
| Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
| Libro (general) | Biblioteca Central UNIBE Área de exhibición | General | 005.7565 G892d (Browse shelf) | Ej.1 | Available | 240397 |
Datos sobre el libro y el autor en la contraportada
Incluye bibliografía
Preface to the Second Edition |
Preface to the First Edition
Introduction |
A crash course in Python |
Visualizing data |
Linear algebra |
Statistics |
Probability |
Hypothesis and inference |
Gradient descent |
Getting data |
Working with data |
Machine learning |
k-Nearest neighbors |
Naive bayes |
Simple linear regression |
Multiple regression |
Logistic regression |
Decision trees |
Neural networks |
Deep learning |
Clustering |
Natural language processing |
Network analysis |
Recommender systems |
Databases and SQL |
MapReduce |
Data ethics |
Go forth and do data science |
Index