Exploratory data analysis

At your disposal is the data of the service Yandex. Apartments for sale in Saint-Petersburg and neighboring settlements for several years. You need to learn how to determine the market value of real estate. Your task is to set the parameters.

Statistical analysis of data

You are an analyst of Megaline, a federal mobile operator. The clients are offered two tariff plans: "Smart" and "Ultra". To adjust the advertising budget, the commercial department wants to understand which tariff brings more money.

Common project

You work in the online store " Streamchik ", which sells around the world computer games. Historical data on game sales, user and expert evaluations, genres and platforms (e.g. Xbox or PlayStation) are available from open sources. You need to identify patterns that determine the success of the game.

Introduction to machine learning

Mobile operator "Megaline" found out: many customers use archive tariffs. They want to build a system that can analyze customer behavior and offer users a new tariff: "Smart" or "Ultra".

Supervised learning

"Beta-Bank" started leaving clients. Every month. A little, but noticeable. Banking marketers thought: it is cheaper to save current customers than to attract new ones. It is necessary to predict whether the client will leave the bank in the near future or not.

Machine learning in business

Suppose you work at GlavRosGosNeft production company. We need to decide where to drill the new well. You have been given samples of oil in three regions: in each region there are 100,000 oil fields where the quality of oil and the volume of its reserves were measured.

Common project 2

Prepare a prototype machine learning model for "Numbers". The company develops solutions for efficient operation of industrial enterprises. The model must predict the recovery rate of gold from gold ore. Data with mining and cleaning parameters are at your disposal.

Linear algebra

You need to protect your customer data from "We're not afraid of the flood" insurance company. Develop a method to convert data so that it is difficult to recover personal information.

Numerical analysis

Car sales service with mileage "Not broken, not painted" develops an application to attract new customers. In it you can quickly find out the market value of your car. Historical data: technical specifications, equipment and prices of cars are at your disposal. You need to build a model to determine

Time Series

"Cool Taxi" Company has collected historical data on taxi orders at airports. To attract more drivers during the peak load, you need to predict the number of taxi orders for the next hour. Build a model for such a prediction.

Machine learning for texts

Online store "Wikishop" launches a new service. Now users can edit and supplement product descriptions, as on wikis. That is, customers offer their edits and comment on changes made by others. The store needs a tool that will search for toxic comments and send them to moderation.

Computer vision

Network supermarket "Bread and salt" introduces a computer vision system for processing photos of customers. Photofixing in the checkout area will help determine the age of customers to: Analyze purchases and offer products that may interest customers of this age group;