### 数学代写|线性代数代写linear algebra代考|МATH 1014

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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 数学代写|线性代数代写linear algebra代考|Basic Math and Calculus Review

We will kick off the first chapter covering what numbers are and how variables and functions work on a Cartesian system. We will then cover exponents and logarithms. After that, we will learn the two basic operations of calculus: derivatives and integrals.
Before we dive into the applied areas of essential math such as probability, linear algebra, statistics, and machine learning, we should probably review a few basic math and calculus concepts. Before you drop this book and run screaming, do not worry! I will present how to calculate derivatives and integrals for a function in a way you were probably not taught in college. We have Python on our side, not a pencil and paper. Even if you are not familiar with derivatives and integrals, you still do not need to worry.

I will make these topics as tight and practical as possible, focusing only on what will help us in later chapters and what falls under the “essential math” umbrella.

This is by no means a comprehensive review of high school and college math. If you want that, a great book to check out is No Bullshit Guide to Math and Physics by Ivan Savov (pardon my French). The first few chapters contain the best crash course on high school and college math I have ever seen. The book Mathematics 1001 by Dr. Richard Elwes has some great content as well, and in bite-sized explanations.

## 数学代写|线性代数代写linear algebra代考|Number Theory

What are numbers? I promise to not be too philosophical in this book, but are numbers not a construct we have defined? Why do we have the digits 0 through 9 , and not have more digits than that? Why do we have fractions and decimals and not just whole numbers? This area of math where we muse about numbers and why we designed them a certain way is known as number theory.

Number theory goes all the way back to ancient times, when mathematicians studied different number systems, and it explains why we have accepted them the way we do today. Here are different number systems that you may recognize:
Natural numbers
These are the numbers $1,2,3,4,5 \ldots$ and so on. Only positive numbers are included here, and they are the earliest known system. Natural numbers are so ancient cavemen scratched tally marks on bones and cave walls to keep records.
Whole numbers
Adding to natural numbers, the concept of ” 0 ” was later accepted; we call these “whole numbers.” The Babylonians also developed the useful idea for place-holding notation for empty “columns” on numbers greater than 9 , such as “10,” “ 1,000 ,” or “1,090.” Those zeros indicate no value occupying that column.
Integers
Integers include positive and negative natural numbers as well as 0 . We may take them for granted, but ancient mathematicians deeply distrusted the idea of negative numbers. But when you subtract 5 from 3, you get $-2$. This is useful especially when it comes to finances where we measure profits and losses. In $628 \mathrm{AD}$, an Indian mathematician named Brahmagupta showed why negative numbers were necessary for arithmetic to progress with the quadratic formula, and therefore integers became accepted.

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。