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Name: Biana Grinshpoon
Type: User
Bio: Data scientist
Name: Biana Grinshpoon
Type: User
Bio: Data scientist
The telecom operator would like to be able to forecast their churn of clients. If it's discovered that a user is planning to leave, they will be offered promotional codes and special plan options. The marketing team has collected some of their clientele's personal data, including information about their plans and contracts.
The objective of this project is to help a supermarket chain to determine the age of a person from a photo in order to help them adhere to alcohol laws by making sure they do not sell alcohol to people underage.
In this project, we need to build a model that will predict the amount of gold recovered from gold ore. The model will help to optimize the production and eliminate unprofitable parameters.
Insurance company wants to solve several tasks with the help of Machine Learning.
A compnay for car sales service is developing an app to attract new customers. In that app, you can quickly find out the market value of your car. You have access to historical data: technical specifications, trim versions, and prices. You need to build the model to determine the value. The company is interested in: the quality of the prediction the speed of the prediction the time required for training
This project contain a data of taxi orders at airports. The aim of this project is to predict the number of taxi orders for the next hours, to attract more drivers at peak hours.
In this project, the main objective is to find the best place out of three regions to develop new 200 oil wells. We will build a model for predicting the volume of reserves in new wells, pick the wells with the highest estimated reserves, and then choose the region with the highest estimated total profit for the selected oil wells.
The customers of the bank are leaving: little by little, chipping away every month. In this project, we need to predict whether a customer will leave the bank soon or not. We will build a model with the maximum possible F1 score - at least 0.59, and also measure the AUC-ROC metric.
In this project, we will analyze the data of a big online store. The store wants to boost its revenues, so the marketing department compiled some hypotheses that may help accomplish this objective. The main goal of this project is to prioritize the hypotheses and analyze the results of the A/B test.
In this project, we will analyze data from a website that sells cars. The data contain information from the different ads that were placed on the site in the past several years, which will help us determine what are the factors that influence the car's price.
In this project, we will use a bankβs data on customers to determine whether their marital status and number of children have an impact on their ability to default on a loan. The conclusions of this project will help later on to build a credit score for potential customers of the bank.
In this project, we will analyze the data of an online store, that sells products of all kinds. The main goal of this project is to get insights that will help us optimize the marketing expenses of the store. To achieve that we are going to conduct a business analysis of the data.
In this project, we will process data of restaurants some market analysis. The goal is to find out whether an innovative restaurant with small robot waiters can maintain its success after its novelty wears off, or is it just a gimmick that will end.
In this project, we are going to analyze the data of a telecom operator. The company offers its users two prepaid plans, which we are going to research and determine which one of them brings more revenue to the company. In the end, the findings will help the commercial department to adjust its budget for advertising campaigns on the most profitable plan.
In this project we will analyze data of an online store that sells food. We will check the users funnel and see how many users make the entire journey from the main screen to the payment screen, and how many are quit in the middle or at the beginning. Also, we will check the results of an A/A/B test that checks whether changing the fonts for the entire app will change the users' behavior and increase revenues or not.
In this project, we will analyze the data of an online store that sells video games all around the world. The data contain users and experts reviews, genres, platforms (e.g. Xbox or PlayStation), and so on. The main goal of this project is to identify patterns that determine whether a game succeeds or not, which will help to spot potential games and recommend the store the best advertising campaign.
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