What do you mean by data mining?

Data mining is the process of discovering patterns, correlations, and insights from large datasets. It involves extracting and analyzing large amounts of data to uncover hidden patterns and valuable information that can be used for various purposes, such as business decision-making, market research, fraud detection, and predictive modeling.

How does data mining work?

Data mining employs various techniques and algorithms to uncover patterns and insights from data. It typically involves the following steps:
• Data collection: Gathering relevant data from various sources, such as databases, websites, and social media platforms.
• Data preprocessing: Cleaning and transforming the raw data to make it suitable for analysis. This may involve removing missing values, dealing with outliers, and normalizing the data.
• Exploratory data analysis: Conducting statistical analysis and visualization to understand the structure and characteristics of the data.
• Model selection: Choosing appropriate data mining algorithms and techniques based on the nature of the problem and the available data.
• Model construction: Applying the selected algorithms to the dataset to create models that capture the patterns and relationships in the data.
• Model evaluation: Assessing the performance of the models in terms of accuracy, precision, recall, or other relevant metrics.
• Deployment: Implementing the developed models to make predictions or support decision-making in real-world applications.