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HypothesisTesting : Statistical Models help test hypotheses by analysing relationships between variables. These models help in hypothesistesting and determining the relationships between variables. Bayesian models and hypothesistests (like t-tests or chi-square tests) are examples of inferential models.
Concepts such as probability distributions, hypothesistesting , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. SupportVectorMachines (SVM) SVMs are powerful classifiers that separate data into distinct categories by finding an optimal hyperplane.
Well-supported: Python has a large community of followers that includes professionals from the academic and industrial circles which allows them to use the analytics libraries for problem solving. Accordingly, it is possible for the Python users to ask for help from Stack Overflow, mailing lists and user-contributed code and documentation.
Inferential Statistics: A branch of statistics that makes inferences about a population based on a sample, allowing for hypothesistesting and confidence intervals. J Jupyter Notebook: An open-source web application that allows users to create and share documents containing live code, equations, visualisations, and narrative text.
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