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Dr. Mint Publication List (English ver)

 Mint Publishing has published the following books.


All of them are easy to understand and carefully explained so that you can understand them from scratch.

The following series are available now.

  • Artificial Intelligence Series 
  • Mathematics Series 
  • Physics Series 
  • Image Processing Series 
  • Numerical Computation and Analysis Series 
  • Python Series 
  • R Series

The series is organized in such a way that you can learn from the one you are interested in, or you can start with the first volume of the series in order. By going back and forth between the series, the content is highly synergistic with each other.

Each of the books is listed below.
(For more information about each book, please visit the respective book page.)


Artificial Intelligence Series 

 [1]. Understanding Perceptrons: A Foundation for Deep Learning

 (coming soon)

 

[2]. Understanding the Improved Perceptron (The Ancestor of Deep Learning)

 

If you want to learn ADALINE, we recommend this book (access here).

 

 

 [3]. Understanding Linear Regression from Scratch

If you want to learn linear regression, we recommend this book (access here).

 

 

[4]. Understanding Logistic Regression from Scratch 

If you want to learn logistic regression, we recommend this book (access here).


[5]. Understanding k-Nearest Neighbors from Scratch

If you want to learn k-Nearest Neighbors (Nearest Neighbor Method), we recommend this book (access here).



[6]. Understanding Multiple Regression from Scratch

If you want to learn multiple regression analysis, we recommend this book (access here).



[7]. Decision Trees A Beginner's Guide

 

If you want to learn decision trees, we recommend this book (access here).



[8]. Understanding the Bootstrap Method from Scratch

 

For those who want to learn the bootstrap method, we recommend this book (access here).

 

 

[9]. Understanding Random Forests from Scratch

 

If you want to learn Random Forest, we recommend this book (access here).



[10]. Understanding Decision Tree Regression from Scratch

 

For those of you who want to learn decision tree regression, we recommend this book (access here).

 

 

[11]. Understanding Support Vector Machines from Scratch

If you want to learn Support Vector Machines, we recommend this book (click here).

 

 

[12]. Understanding AdaBoost from Scratch

If you want to learn AdaBoost, we recommend this book (access here).

 

[13]. Understanding k-Nearest Neighbor Regression from Scratch 

If you’re interested in learning k-Nearest Neighbor Regression, we recommend this book (access here).

 

 

[14]. Understanding Random Forest Regression from Scratch

If you are interested in learning Random Forest Regression, we recommend this book (access here).

 

 

[15]. Understanding Support Vector Regression from Scratch

If you want to learn Support Vector Regression, we recommend this book (access here).

 

 

[16]. Understanding Cluster Analysis from Scratch: K-Means Method ①


If you want to learn the k-means method, we recommend this book (click here for access).

 

 

[17].  Understanding Principal Component Analysis from Scratch

 (coming soon)

 

[18]. Understanding Data Visualization from Scratch

(coming soon)

 

[19]. Understanding Descriptive Statistics from Scratch 

 (coming soon)

 

[20]. Understanding Probability and Probability Distributions from Scratch 

 (coming soon)

 

[21]. Understanding Sample Surveys and Estimation: From Zero to Proficiency 

 

If you want to learn about sample surveys and estimation, we recommend this book (access here).

 

 

Mathematics Series  

 [1]. Understanding Trigonometry from Scratch: Sine, Cosine, and Tangent

 If you want to learn trigonometry, we recommend this book (access here).

 
 

[2]. Understanding Exponential Functions from Scratch 

 

If you want to learn exponential functions, we recommend this book (click here for access).

 

 

[3]. Understanding Logarithmic Functions from Scratch

 

If you want to learn logarithmic functions, we recommend this book (click here).



[4]. Understanding Reciprocal Functions from Scratch

 

If you want to learn about reciprocal functions, we recommend this book (click here to access).



[5]. Understanding Differential Equations of Separable Variables from Scratch

If you want to learn about ‘differential equations’ of separable variables, we recommend this book (access here).



[6]. Understanding Hyperbolic Functions from Scratch

If you want to learn about the "differential equations" of hyperbolic functions, we recommend this book (access here).

 
 

[7]. Understanding Differential Equations Solved with Variation of Parameters

 

If you want to learn more about solving differential equations with variation of parameters, we recommend this book (access here).



[8]. Understanding Linear Differential Equations with Constant Coefficients

If you're interested in learning linear differential equations with constant coefficients, we recommend this book (click here).

 

 

Physics Series 

 (coming soon)
 
 

Image Processing Series 

[1]. Environment Building for Image Processing 

If you want to learn Image processing, we recommend this book (access here).
 

 

 [2]. First Steps in Image Processing Basics

If you want to learn Image processing, we recommend this book (access here).



[3]. Image Binarization

If you’re interested in the world of binarization, please refer to the following books! (access here)

 

 

[4]. What is Image Representation? 

 (coming soon)

 

[5]. What is Image Compression?

 

If you've become interested in learning about image compression, please refer to the following books as well! (access here)

 

 

 

 Numerical Computation and Analysis Series 

 [1]. Understanding Interpolation from Scratch

If you’re interested in learning interpolation, we recommend this book (click here for access).

 

 

[2]. Understanding the Euler Method from Scratch 

 


If you're interested in learning the Euler method, we recommend this book (access here).

 
 

[3]. Understanding the Modified Euler Method (Heun's Method) from Scratch

If you want to learn the Modified Euler Method (Heun's Method), we recommend this book (access here).

 

 

Python Series 

 (coming soon)
 
 

R Series

(coming soon) 
 
 
 

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Understanding the Modified Euler Method (Heun's Method) from Scratch

This article explains the basic concepts, applications, and benefits of learning the Modified Euler Method (Heun's Method). This method, a step forward from the simple Euler method, plays a very important role in the world of numerical analysis. 1. What is the Modified Euler Method (Heun's Method)? The Modified Euler Method, also known as Heun’s Method, is a numerical method for obtaining approximate solutions to initial value problems: dy/dt = f(t, y), y(t_0) = y_0 The traditional Euler method determines the next value, y_{n+1}, using only the slope of the tangent line at time t_n, namely f(t_n, y_n).  However, when the step size is large or the problem exhibits strong non-linearity, this can lead to significant errors. A key feature of Heun’s Method is its ability to achieve higher accuracy (local error of second order) through a two-stage evaluation process, improving upon the Euler method. 2. In What Scenarios is it Applied? Due to its simplicity and improved accuracy, Heun...
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Lista de publicaciones del Dr. Mint (en inglés)

   Mint Publishing ha publicado los siguientes libros. Todos ellos son fáciles de entender y están cuidadosamente explicados para que puedas comprenderlos desde cero. Las siguientes series ya están disponibles.   Serie Inteligencia Artificial   Serie Matemáticas   Serie Física   Serie Procesamiento de Imágenes   Serie Cálculo y Análisis Numérico   Serie Python   Serie R Las series están organizadas de tal manera que puedes aprender de la que más te interese, o puedes empezar con el primer volumen de la serie en orden. Al ir y venir entre las series, el contenido es altamente sinérgico entre sí. A continuación se enumeran los libros. (Para más información sobre cada libro, visite la página del libro correspondiente).   Serie Inteligencia Artificial   [1]. Entendiendo los perceptrones : Una base para el aprendizaje profundo  (próximamente) [2]. Understanding the Improved Perceptron (El...
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Understanding Reciprocal Functions from Scratch

The reciprocal function is one of the fundamental functions in mathematics, and despite its simplicity, it’s a powerful tool with applications in many fields thanks to its unique characteristics. This article will provide a detailed explanation of the definition and properties of reciprocal functions, explore the contexts in which they are used, and outline the benefits of learning about them. 1. What is a Reciprocal Function? A reciprocal function returns the reciprocal of a given real number.  - Graph Shape The graph of a reciprocal function forms a hyperbola, with values increasing or decreasing rapidly as it approaches the origin. It takes the shape of a hyperbola spanning the first and third quadrants, and has asymptotes at x = 0 and y = 0. Behind this simple equation lies the concept of a multiplicative inverse, which forms the foundation of basic algebra. 2. Where are Reciprocal Functions Used? Due to their fundamental nature and simplicity, reciprocal functions are used in ...
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