Concept of Data Mining: Data Collection: Data mining begins with the collection of large volumes of structured or unstructured data from diverse sources, such as databases, websites, sensors, social media, and transactional systems. Data Preprocessing: The collected data undergoes preprocessing to clean, transform, and prepare it for analysis. This may involve removing duplicates, handling missing values, standardizing data formats, and normalizing data distributions. - Data Analytics Online Training Exploratory Data Analysis (EDA): EDA techniques are used to explore the dataset visually and statistically, identifying patterns, correlations, and outliers that may provide valuable insights. Model Building: Data mining algorithms are applied to the preprocessed data to build predictive or descriptive models that capture underlying patterns and relationships. These algorithms include classification, regression, clustering, association rule mining, and anomaly detection tech...
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