"Not my answer, but rather the details of this question. It should include the following functions:
int insertNewCustomer(double revenue) -> returns a customer ID (assume auto-incremented & 0-based)
int insertNewCustomer(double revenue, int referrerID) -> returns a customer ID (assume auto-incremented & 0-based)
Set getLowestKCustomersByMinTotalRevenue(int k, double minTotalRevenue) -> returns customer IDs
Note: The total revenue consists of the revenue that this customer bring"
Anzhe M. - "Not my answer, but rather the details of this question. It should include the following functions:
int insertNewCustomer(double revenue) -> returns a customer ID (assume auto-incremented & 0-based)
int insertNewCustomer(double revenue, int referrerID) -> returns a customer ID (assume auto-incremented & 0-based)
Set getLowestKCustomersByMinTotalRevenue(int k, double minTotalRevenue) -> returns customer IDs
Note: The total revenue consists of the revenue that this customer bring"See full answer
"You should identify this type of interview question as an Expansion problem, since we're asked to expand further into a market. This is similar to a growth problem, with a few additional components. This is the formula you should use when tackling these types of interview questions:
Ask clarifying questions
Perform user analysis
Market risk analysis
State goals
Perform channel analysis
Prioritize growth channels
Strategy
Summarize
With"
Exponent - "You should identify this type of interview question as an Expansion problem, since we're asked to expand further into a market. This is similar to a growth problem, with a few additional components. This is the formula you should use when tackling these types of interview questions:
Ask clarifying questions
Perform user analysis
Market risk analysis
State goals
Perform channel analysis
Prioritize growth channels
Strategy
Summarize
With"See full answer
"Random Forest is a machine learning model used for classification problems or regression problems. It can handle binary classification as well as multi-class classification. It is a very efficient model and is great for a baseline or used in a service that needs extremely low latency depending on the size of the model. It's also a good option for wide datasets (dataset with many features) due to it's random subset of features. it is slightly less optimized for deep datasets on very large dataset"
Jake M. - "Random Forest is a machine learning model used for classification problems or regression problems. It can handle binary classification as well as multi-class classification. It is a very efficient model and is great for a baseline or used in a service that needs extremely low latency depending on the size of the model. It's also a good option for wide datasets (dataset with many features) due to it's random subset of features. it is slightly less optimized for deep datasets on very large dataset"See full answer