R MAKİNE ÖĞRENMESİ VERİ YAPILARI | R MACHINE LEARNING

In the 4th video of our machine learning training series with R, we discussed data structures, one of the important topics of machine learning. Data structures are structures that enable data to be organized and stored in a specific format and are used to analyze and process different types of data. The functions and purposes of data structures in R are as follows: 1. Vector: Function: Represents an ordered collection of data of the same type. Areas of Use: It is used to create simple data sets, perform numerical calculations, filter data and perform basic statistical analysis. For example, vectors can be used to store the ages of a group of people or the results of an experiment. 2. Matrix: Function: It is a two-dimensional arrangement of numerical data, the data is placed in rows and columns. Uses: Can be used for linear algebra operations (matrix multiplication, transpose), image processing or data analysis (e.g. creating correlation matrices). 3. Array: Function: It allows storing data in a multidimensional way, it is an n-dimensional arrangement of data of the same type. Areas of Use: It can be used to represent multidimensional data, for example in time series analysis or image processing. 4. Data Frame: Function: It stores different types of data in columns, and each column represents a variable and each row represents an observation. Uses: It works like a database table and is very useful for data analysis, statistical modeling and machine learning. Data frames are preferred when it is necessary to keep various types of data together (for example, storing different types of data such as age, name and gender). 5. List: Function: It is a flexible data structure that can bring together multiple and different types of data. Areas of Use: It is used when it is necessary to store different data types together. For example, lists are preferred for the results of a model (summary statistics, predictions, error rates) or in projects involving complex data structures (for example, data frame and vector combinations). Factor 6: Function: It represents categorical data and contains classes called levels. Areas of Use: When working with categorical variables, it is used in analyzes where data are grouped or classified according to a certain class (for example, expressing survey results with categorical values ​​such as "Male/Female" or "Low/Medium/High"). Each data structure better supports a specific data type or analysis purpose, making data manipulation, analysis, and modeling in R more effective. WHAT IS MACHINE LEARNING? | HOW DOES A MACHINE LEARN? -- To access the resources used in the course, GitHub: https://github.com/merhabayazilim01/R... --Instagram: @merhabayazilim01 --LinkedIn: Merhaba Yazılım Instructor: Hasan Can Demirci Editor: Naz Balcı