Publications by Thanh Dat
Support Vector Machines in R
Support Vector Machines in R 1 Introduction 1.1 Sugar content of soft drinks 1.2 Linearly separable dataset 2 Linear Kernels 2.1 Linear SVM 2.2 Visualizing Linear SVMs 2.3 Tuning linear SVMs 2.4 Multiclass problems 3 Polynomial Kernels 3.1 Radially separable dataset 3.2 Linear SVMs on radial data 3.3 The kernel trick 3.4 Tuning SVMs 4 Radi...
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Introduction to Rmarkdown
Introduction to Rmarkdown 1 Components of a Markdown file 1.1 YAML header 1.2 Customizing the report style 1.3 Header 1.4 Paragraphs 1.5 Blockquotes 1.6 Lists 1.7 Images 1.8 Code chunk 1.9 Referencing code 1.10 Code chunk options 1.11 Printing table 2 rmdformats 2.1 Installation 2.2 Creating a new document 2.3 Formats gallery 2.4 Options Tr...
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Modeling with Data in the Tidyverse
Modeling with Data in the Tidyverse 1 Introduction to Modeling 1.1 Background on modeling for explanation 1.2 Background on modeling for prediction 1.3 The modeling problem for explanation 1.4 The modeling problem for prediction 2 Modeling with Basic Regression 2.1 Explaining teaching score with age 2.2 Predicting teaching score using age 2.3...
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Working with Data in the Tidyverse
Working with Data in the Tidyverse 1 Explore your data 1.1 Import your data 1.2 Know your data 1.3 Count with your data 2 Tame your data 2.1 Cast column types 2.2 Recode values 2.3 Select variables 2.4 Tame variable names 3 Tidy your data 3.1 Introduction to Tidy Data 3.2 Gather 3.3 separate() 3.4 spread() 3.5 Tidy multiple sets of columns ...
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Reshaping Data with tidyr
Reshaping Data with tidyr 1 Tidy data 1.1 What is tidy data? 1.2 Columns with multiple values 1.3 Missing values 2 From wide to long and back 2.1 From wide to long data 2.2 Deriving variables from column headers 2.3 Deriving variables from complex column headers 2.4 From long to wide data 3 Expanding data 3.1 Creating unique combinations of...
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Machine Learning in the Tidyverse
Machine Learning in the Tidyverse 1 Foundations of “tidy” Machine learning 1.1 "Tidy" machine learning 1.2 The map family of functions 1.3 Tidy your models with broom 2 Multiple Models with broom 2.1 Coefficients across models 2.2 The fit of many models 2.3 Inspect many models 2.4 Improve the fit of your models 3 Build, Tune & Evaluate R...
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Probability Puzzles in R
Probability Puzzles in R 1 Introduction and Classic Puzzles 1.1 Introduction to the Course 1.2 The Birthday Problem 1.3 Monty Hall 2 Games with Dice 2.1 Yahtzee 2.2 Settlers of Catan 2.3 Craps 3 Inspired from the Web 3.1 Factoring a Quadratic 3.2 Four Digit iPhone Passcodes 3.3 Sign Error Cancellations 4 Poker 4.1 Texas Hold’em 4.2 Cons...
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Exploring the Kaggle Data Science Survey
Exploring the Kaggle Data Science Survey 1 Welcome to the world of data science 2 Using multiple tools 3 Counting users of each tool 4 Plotting the most popular tools 5 The R vs Python debate 6 Plotting R vs Python users 7 Language recommendations 8 The most recommended language by the language used 9 The moral of the story Tran Thanh Dat - In...
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Introduction to Python
Introduction to Python 1 Python Basics 1.1 Hello Python! 1.2 Variables and Types 2 Python Lists 2.1 Python Lists 2.2 Subsetting Lists 2.3 Manipulating Lists 3 Functions and Packages 3.1 Functions 3.2 Methods 3.3 Packages 4 NumPy 4.1 Numpy 4.2 2D Numpy Arrays 4.3 Numpy: Basic Statistics Tran Thanh Dat - International University 25 Febr...
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Intermediate Python
Intermediate Python 1 Matplotlib 1.1 Basic plots with Matplotlib 1.2 Histogram 1.3 Customization 2 Dictionaries & Pandas 2.1 Dictionaries, Part 1 2.2 Motivation for dictionaries 2.3 Dictionaries, Part 2 2.4 Pandas, Part 1 2.5 Pandas, Part 2 3 Logic, Control Flow and Filtering 3.1 Comparison Operators 3.2 Boolean Operators 3.3 if, elif, else...
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