Applied machine learning with Python

by Giussani, Andrea

Type Book

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Title Statements

Full title :Applied machine learning with Python / Andrea Giussani.

Edition Statements

Publication Date:2020.

Publication Statements

Publisher(s):Bocconi University Press
Place of Publication:Milano
Language:eng
Publication Date:2020.

The Physical Object

Description:1 ressource en ligne

Edition Identifiers

ISBN:8831322141, 9788831322140
oclc:on1259013340
LC Classification:Q325.5
Dewey Decimal:006.31

APPLIED MACHINE LEARNING WITH PYTHON -- Contents -- List of Figures -- Preface -- Chapter 1. Introduction to Machine Learning -- 1.1 A simple supervised model: Nearest Neighbor -- 1.2 Preprocessing -- 1.3 Methods for Dealing with Imbalanced Data -- 1.4 Reducing Dimensionality: Principal Component Analysis -- Chapter 2. Linear Models for Machine Learning -- 2.1 Linear Regression -- 2.2 Shrinkage Methods -- 2.3 Robust Regression -- 2.4 Logistic Regression -- 2.5 Linear Support Vector Machine -- 2.6 BeyondLinearity: Kernelized Models

Appendix B. Mathematics behind the skip-gram model -- Index -- Bibliography -- Back Cover

Chapter 3. Beyond Linearity: Ensemble Methods for Machine Learning -- 3.1 Introduction -- 3.2 Ensemble Methods -- 3.3 Random Forests -- 3.4 Boosting Methods -- Chapter 4. An Introduction to Modern Machine Learning Techniques -- 4.1 Introduction to Natural language Processing -- 4.2 Introduction to Deep Learning -- Appendices -- Appendix A.A crash course in Python -- A.1 Building Blocks in Python -- A.2 Data Structure in Python -- A.3 Loops in Python -- A.4 Advanced Data Structure in Python -- A.5 Advanced Concepts on Functions -- A.6Introduction to Object-Oriented…