Machine Learning Zoomcamp Update: Thursday, 23 September 2021
Date: 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(W_{0} + W^{T}x_{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