Foundations of Data Science.
Understanding Maximum Likelihood estimation, Beta distribution, Calculation of posterior probability.
Implementing Gradient descent and Stochastic gradient descent from scratch to build linear regression models.
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Foundations of Data Science. Linear regression, Logistic Regression implemented from scratch. Lasso and Ridge regression.
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