Aniket Sharma

Machine Learning Zoomcamp Update: Thursday, 23 September 2021

Today, I completed the Sessions 3.9, 3.10, 3.11 and 3.12.

Session 3.9 - Logistic regression

This session explained Logistic Regression.

Key takeaways:

• Logistic regression is similar to linear regression, just the sigmoid function is applied to change the range of output and converting the output to probabilities.
• g(x_i) = sigmoid(W₀ + W^Tx_i)

Session 3.10 - Training logistic regression with Scikit-Learn

This session trained a binary classification model using LogisticRegression in scikit-learn.

Session 3.11 - Model interpretation

This session explained how we can observe the weights of a model to interpret how the model works and which features affect the model in which way.

Session 3.12 - Using the model

This session re-trains the model using combined dataset (training + validation) and uses it to predict value sof the test set.

Estimated Time Taken: 45 minutes