Linear algebra is a useful tool with many applications in computer science. This article will cover the various applications of linear algebra in computer science, including: Internet search, graphics, speech recognition, and artificial intelligence. One of the main purposes of linear algebra in computer science is Internet searching, which involves finding techniques to store and search information efficiently. In 2000, there were approximately 2.5 billion web pages on the Internet, with a growth rate of 7.3 million per day. . Linear algebra is used in organizing and sorting these web pages when storing them in an Internet search database. The vector spatial model is used to improve search results by representing them as two vectors, the document vector and the query vector. Each dimension of the vector corresponds to a different term. If the term appears in the document, its value in the vector is a non-zero value. Several different methods of calculating term weights have been developed, one of which is inverse document weight frequency (tf-idf). The frequency part if td-idf refers to the frequency of the term in the document. Inverse document frequency is the log function of the total number of documents / divided by the number of documents in which the term appears. The inverse frequency document template simply multiplies these 2 values. Using the cosine similarity between the document and the query vector allows the computer to group data together or generate similar data. The main advantages of using this model over the standard Boolean model are that it allows documents to be ranked based on their relevance and that it allows partial matching. There are a large number of variations of ...... middle of paper ...... in statistical machine learning, these are probability distributions and parameter spaces that are represented at vector help. Currently, the use of linear algebra in AIs can be avoided when using prepared libraries, but to understand how and why the algorithms work in the AI ​​unit, you will need linear algebra. Linear algebra has a big impact on the field of computer science and is one of the most important tools to learn if you want to excel in computer science. Linear algebra has its effects in a large number of applications in computer science, but its most significant impacts are its use to organize and sort large quantities of web pages in the Internet search database, its ability to transform graphic images, its impact on voice recognition, and finally its ability to provide AI with the concept of statistical machine learning.