Materials Data Science

Table of Contents

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   Book Overview
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   Chapter 1 A Brief History of Data and Data Science
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   Chapter 2 From Data Science to Materials Data Science
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   Chapter 3 What You Should Know About Data, Math, and Computing
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   Chapter 4 Materials Science Datasets and Data Generation
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   Chapter 5 Combinatorics and Probabilities
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   Chapter 6 Random Variables and Probability Functions
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   Chapter 7 Expectation, Variance, and Moments
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   Chapter 8 Introduction to Statistics
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    Chapter 9 Exploratory Data Analysis
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    Chapter 10 Commonly Encountered Distributions in Materials Science and Engineering
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    Chapter 11 Introduction and General Concepts of Machine Learning and Data Science
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    Chapter 12 A First Approach to Machine Learning with Linear Regression
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    Chapter 13 Advanced Methods and Topics of Regression
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    Chapter 14 Supervised Classification
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    Chapter 15 Unsupervised Learning
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    Chapter 16 Machine Learning Techniques
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    Chapter 17 From the Perceptron to Artificial Neural Networks
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    Chapter 18 A Gentle Introduction to Deep Learning
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    Chapter 19 Advanced Deep Learning Architectures and Techniques