Lulude presentations about logistic regression. She outlines the similarities and the differences between logistic and linear regression. Next, she wrote the advantages and the disadvantages of logistical regression. She gave examples such as: logistical regression is easier to implement than other regressions. Also, one of the disadvantages she gave was that it cannot solve linear problems. She taught us about the uses for logical regression and gave us different applications for logical regression. Some of the application she explained to us were the use of log odds, sigmoid, and gradient dissent. She informed us that we could use logical regression to load data sets and make predictions. She also showed us how to visualize and explore data using logical regression.