Decorators in Python

-  Tell me the difference between the maximum margin classifier and the hyperplane. A hyperplane is a straight line that separates linearly separable data into two classes. If data can be separated that way, it means an infinite number of hyperplanes can be drawn in the space between two data classes. Any such straight line is a hyperplane. The maximum margin classifier's purpose is to select the best possible hyperplane. The margins are lines that go through the nearest point from each class. The maximum margin classifier is the hyperplane with the maximum distance from the training observations, meaning the point where the margin is drawn.

 GBM  NaiveBayes - difference between logit and probit models? The main difference between the logit and probit models is the assumption of the distribution of the errors in a model. The logit model follows the cumulative distribution function of the  logistic distribution , while the probit model uses the cumulative distribution function of the  standard normal distribution . - KNN - Regression : regression is way to find coefficients to fit into the equation, or how many apples to get to fit into a basket - Random Forest vs Gradient Boosting - asked in HDW Random forest is a supervised learning algorithm that utilizes multiple decision trees. Decision trees are made of decision nodes which further lead to either another decision node or a final value (leaf node). Gradient boosting tree uses boosting algorithm. Boosting algorithm trains a sequence of weaker models to increase the accuracy of the overall model by learning from the previous model. Random Forest is a b...

 System Design Q:  Describe how would you approach a task of automating traffic lights. What factors will influence your choice of how much time to allocate for each phase of a cycle? Q: Given data on Meta/Facebook members friending/defriending each other on Meta/Facebook, find out whether a given pair of members are currently friends. Q: How would you design a database schema for storing customers' address information, given that the address of some customers changes in time? Q: How would you compare the relative performance of two different backend engines for automated generation of Meta/Facebook "Friend" suggestions? Q: On e-commerce websites, such as Amazon, users sometimes want to buy products that are out of stock. How would you design a recommendation system to suggest the replacement for these products?