emmanuel-123tech Goto Github PK
Name: Emmanuel Ebiendele
Type: User
Bio: A creative Graphic Designer, Digital Marketer & a certified data scientist with minimum of 2years work experience
Twitter: HemmyBoy4
Location: Nigeria
Name: Emmanuel Ebiendele
Type: User
Bio: A creative Graphic Designer, Digital Marketer & a certified data scientist with minimum of 2years work experience
Twitter: HemmyBoy4
Location: Nigeria
Predict the likelihood of a lead reaching the last stage (onboarding) quicker than others. This will enable the team to channel resources and efforts toward converting such leads. The model that says the type of leads to after, so we don’t waste resources. (In terms of age, geography, marital status, and other lead qualities) Your task is to build machine learning to help the business in saving costs. Note: Maximum Submission per day Predict the likelihood of a lead reaching the last stage (onboarding) quicker than others. This will enable the team to channel resources and efforts toward converting such leads. The model that says the type of leads to after, so we don’t waste resources. (In terms of age, geography, marital status, and other lead qualities) Your task is to build machine learning to help the business in saving costs. Note: Maximum Submission per day is 20. Kindly have good cross validation to optimise your solution and submission.
Can you use tourism survey data and ML to classify the range of expenditures a tourist spends in Tanzania?
Can you use tourism survey data and ML to classify the range of expenditures a tourist spends in Tanzania?
First place solution form Ansem Chaieb.
Predict the likelihood of a lead reaching the last stage (onboarding) quicker than others. This will enable the team to channel resources and efforts toward converting such leads. The model that says the type of leads to after, so we don’t waste resources. (In terms of age, geography, marital status, and other lead qualities) Your task is to build machine learning to help the business in saving costs. Note: Maximum Submission per day Predict the likelihood of a lead reaching the last stage (onboarding) quicker than others. This will enable the team to channel resources and efforts toward converting such leads. The model that says the type of leads to after, so we don’t waste resources. (In terms of age, geography, marital status, and other lead qualities) Your task is to build machine learning to help the business in saving costs. Note: Maximum Submission per day is 20. Kindly have good cross validation to optimise your solution and submission.
An application of a classification problem - Fraud Detection Electricity and Gas Consumption Challenge
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Fraud Detection for online payment
Classifying whether a transaction was Fraud
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