Key tools and techniques in the data science sector include programming languages like Python and R, which are essential for data manipulation, analysis, and visualization. Machine learning algorithms (ML Algorithms), such as decision trees, neural networks, and k-means clustering, are used to model and predict data patterns. Data wrangling and cleaning techniques are crucial for…
Data Science combines statistical analysis, machine learning, and data processing to extract insights from large data sets. Popular use cases include recommendation systems in streaming services, fraud detection in finance, predictive maintenance in manufacturing, customer sentiment analysis, and personalized marketing, enhancing decision-making and improving user experiences across industries. What is Data Science: Its Popular Use…
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