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Statistical Concepts A strong understanding of statistical concepts, including probability, hypothesistesting, regression analysis, and experimental design, is paramount in Data Science roles. It forms the basis for many statistical tests and estimators used in hypothesistesting and confidence interval estimation.
Familiarity with cloudcomputing tools supports scalable model deployment. Concepts such as probability distributions, hypothesistesting , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions.
Hypothesistesting and regression analysis are crucial for making predictions and understanding data relationships. Machine Learning Supervised Learning includes algorithms like linear regression, decisiontrees, and support vector machines.
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