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5026 مرتبه مشاهده شده
Python for probability, statistics, and machine learning
Unpingco, Jose.
- ISBN:3319307150
- ISBN:9783319307152
- Call Number : QA 76 .73 .P98 .U56 2016
- Main Entry: Unpingco, Jose.
- Title:Python for probability, statistics, and machine learning [electronic resource] / Jose Unpingco.
- Publisher:Switzerland : Springer, 2016.
- Physical Description:xiv, 276 p.: ill ; 25 cm
- Notes:Includes bibliographical references and index
- Subject:Machine learning.
- Subject:Probabilities -- Data processing.
- Subject:Python (Computer program language)
- Subject:Statistics -- Data processing.
Python for probability, statistics, and machine learning
- Preface
- Contents
- Notation
- About the Author
- 1 Getting Started with Scientific Python
- 2 Probability
- 2.1 Introduction
- 2.2 Projection Methods
- 2.3 Conditional Expectation as Projection
- 2.4 Conditional Expectation and Mean Squared Error
- 2.5 Worked Examples of Conditional Expectation and Mean Square Error Optimization
- 2.6 Information Entropy
- 2.7 Moment Generating Functions
- 2.8 Monte Carlo Sampling Methods
- 2.9 Useful Inequalities
- References
- 3 Statistics
- 3.1 Introduction
- 3.2 Python Modules for Statistics
- 3.3 Types of Convergence
- 3.4 Estimation Using Maximum Likelihood
- 3.5 Hypothesis Testing and P-Values
- 3.6 Confidence Intervals
- 3.7 Linear Regression
- 3.8 Maximum A-Posteriori
- 3.9 Robust Statistics
- 3.10 Bootstrapping
- 3.11 Gauss Markov
- 3.12 Nonparametric Methods
- References
- 4 Machine Learning
- Index