Amazon MX Player Production Analyst Interview Questions and Answers

To understand the supply of restaurants in a particular area of a city, we can use various methods.

• Collect data from online directories like Yelp, Zomato, etc.

• Conduct surveys to gather information about the number of restaurants in the area.

• Analyze the population density and demographics of the area to estimate the demand for restaurants.

• Check the number of restaurant permits issued by the local government.

• Use GIS mapp...read more

The weight of an aircraft is crucial for its performance and safety.

• The weight of an aircraft includes the weight of the aircraft itself, fuel, passengers, cargo, and any other equipment on board.

• The weight of an aircraft is measured in pounds or kilograms.

• The weight of an aircraft affects its takeoff and landing performance, as well as its fuel efficiency and range.

• Aircraft manufacturers provide maximum takeoff and la...read more

SQL query to get top 100 Uber drivers by city

• Join drivers and users tables on city

• Aggregate driver ratings and count of rides

• Order by rating and count of rides

• Limit to top 100

Optimizing the listing of Restaurants on Swiggy involves using data-driven strategies to improve visibility, relevance, and user experience.

• Analyze user behavior and preferences to understand their needs and preferences

• Implement a ranking algorithm based on factors like ratings, reviews, popularity, and delivery time

• Optimize search functionality to ensure accurate and relevant results

• Collaborate with restaurants to imp...read more

Linear Regression is used for continuous data while Logistic Regression is used for categorical data.

• Linear Regression predicts continuous values while Logistic Regression predicts probabilities.

• Linear Regression uses a straight line to fit the data while Logistic Regression uses an S-shaped curve.

• Linear Regression uses Mean Squared Error as the cost function while Logistic Regression uses Log Loss.

• Linear Regression is...read more

Bias-Variance trade-off is the balance between overfitting and underfitting. High bias models are simple but inaccurate, low variance models are complex but overfit.

• Bias-Variance trade-off is a fundamental concept in machine learning.

• High bias models are simple and have low variance, but are inaccurate.

• Low bias models are complex and have high variance, but can overfit the data.

• Examples of high bias models are linear r...read more

Possible reasons for a car manufacturer's decline in profits by 40% year over year

• Decreased demand for cars due to economic downturn

• Increased competition from other car manufacturers

• Rising production costs and expenses

• Decline in consumer confidence and spending

• Changes in government regulations impacting the automotive industry