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You have been called in by Abdullah to use your machine learning skills to study the pattern of promotion. With this insight, he can understand the important features among available features that can be used to predict promotion eligibility.

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1

AXA-MANSARD-CHALLENGE

Recently, there has been an increase in the number of building collapse in Lagos and major cities in Nigeria. Olusola Insurance Company offers a building insurance policy that protects buildings against damages that could be caused by a fire or vandalism, by a flood or storm. You have been appointed as the Lead Data Analyst to build a predictive model to determine if a building will have an insurance claim during a certain period or not. You will have to predict the probability of having at least one claim over the insured period of the building. The model will be based on the building characteristics. The target variable, Claim, is a: 1 if the building has at least a claim over the insured period. 0 if the building doesn’t have a claim over the insured period. 11th Position on the Leaderboard
Jupyter Notebook
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2

Video_Games-Sales-Prediction

The gaming industry is certainly one of the thriving industries of the modern age and one of those that are mostly influenced by the advancement in technology. With the availability of technologies like AR/VR in consumer products like gaming consoles and even smartphones, the gaming sector shows great potential. In this hackathon, you as a data scientist must use your analytical skills to predict the sales of video games depending on given factors. Given 8 distinguishing factors that can influence the sales of a video game. Your objective as a data scientist is to build a machine learning model that can accurately predict the sales in millions of units for a given game.
Jupyter Notebook
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