First things first, let's talk about data mining. This technique involves extracting useful information from large data sets to identify patterns and relationships.
Next up, we have text mining. This technique focuses on analyzing unstructured data such as emails, social media posts, and customer feedback to gain insights into customer behavior.
Moving on to web mining, which involves extracting data from the web to identify trends and patterns in consumer behavior.
Another technique is predictive modeling, which uses statistical algorithms to predict future outcomes based on historical data.
Clustering is a technique that groups similar data points together based on their characteristics, helping businesses identify target markets and customer segments.
Association rule mining is a technique that identifies relationships between different data points, helping businesses understand the factors that influence customer behavior.
Decision trees are a visual representation of decision-making processes, helping businesses make informed decisions based on data.
Neural networks are a machine learning technique that mimics the human brain, helping businesses identify patterns and make predictions based on complex data sets.
Bayesian networks are another machine learning technique that uses probability to make predictions based on historical data.
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