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Essential Statistical Tests For Statistical Significance in Machine Learning
Must know statistical tests for testing statistical significance in Machine Learning and Data Science: One-sided & Two-sided T-test, F-test, 2 Sample Z-test, 2 Sample T-test, Chi-Squared test
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Bias-Variance Trade-Off, Overfitting and Regularization in Machine Learning
Introduction to bias-variance trade-off, overfitting and how to solve overfitting using regularization: Ridge and Lasso Regressions.
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Data Sampling Methods in Python
Must know statistical tests for testing statistical significance in Machine Learning and Data Science: One-sided & Two-sided T-test, F-test, 2 Sample Z-test, 2 Sample T-test, Chi-Squared test
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Complete Guide to A/B Testing Design, Implementation and Pitfalls
End-to-end A/B testing for your Data Science experiments for non-technical and technical specialists with examples and Python implementation
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Fundamentals Of Statistics For Data Scientists and Analysts
Key statistical concepts for your data science or data analysis journey with Python Code. Knowing the fundamentals of these two important subjects will allow you to think critically, and be creative when using the data to solve business problems and make data-driven decisions.