[Coursera] Coding the Matrix: Linear Algebra through Computer Science Applications

When you take a digital photo with your phone or transform the image in Photoshop, when you play a video game or watch a movie with digital effects, when you do a web search or make a phone call, you are using technologies that build upon linear algebra. Linear algebra provides concepts that are crucial to many areas of computer science, including graphics, image processing, cryptography, machine learning, computer vision, optimization, graph algorithms, quantum computation, computational biology, information retrieval and web search. Linear algebra in turn is built on two basic elements, the matrix and the vector. In this class, you will learn the concepts and methods of linear algebra, and how to use them to think about problems arising in computer science. You will write small programs in the programming language Python to implement basic matrix and vector functionality and algorithms, and use these to process real-world data to achieve such tasks as: two-dimensional graphics transf

当您使用手机拍摄数码照片或在Photoshop中处理图像，当您玩电子游戏或观赏带有数字效果的影片，当您进行网络搜索或拨打电话时，您正在使用建立在线性代数基础之上的技术。线性代数为计算机科学的众多领域提供了至关重要的概念，包括图形学、图像处理、密码学、机器学习、计算机视觉、优化、图算法、量子计算、计算生物学、信息检索和网络搜索。线性代数本身又建立在两个基本元素之上，即矩阵和向量。在本课程中，您将学习线性代数的基本概念与方法，并探讨如何运用这些知识来思考计算机科学领域出现的各类问题。您将使用Python编程语言编写小程序以实现基本的矩阵和向量功能及其算法，并利用这些工具处理现实世界数据，以完成诸如二维图形转换等任务。