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Linear algebra: Linear algebra is used to represent data, train models, and make predictions.
Calculus: Calculus is used to optimize ml models and understand their behavior.
Probability and statistics: Probability and statistics are used to understand the uncertainty in data and to evaluate the performance.
Statistics
Descriptive statistics: Descriptive statistics are used to summarize and describe data.
Inferential statistics: Inferential statistics are used to draw conclusions about a population based on a sample.
Ml algorithms: Ml algorithms are statistical models that are trained on data to learn patterns and make predictions.
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