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Data Science

Data science is a modern discipline for working with information. It allows obtaining the necessary data for their further analysis, processing and use for specific purposes.

The task of a specialist is a thorough processing of data sets and obtaining a predictable result. The result of the research is a model, which is an algorithm for further actions in solving the problem. A model is a model that is an algorithm for further actions in solving the task.

Basic principles

Data science is based on mathematics. The methods of linear algebra, statistics, optimization are mainly used to work with data. Data science is based on mathematics.

The procedure of Data science consists of 5 main stages:

  1. Data collection. The purpose of the collection, the required amount of data and the methods by which the information will be obtained are defined.
  2. Preparation. Formation of the actual database, its validation.
  3. Formation of the actual database, its validation.

  4. Processing. Separation of information, determination of the methods to be used in the work for a particular task.
  5. Analysis. Data science project processing – analysis, prediction on the basis of obtained data. For each specific research Data science project is created. It necessarily includes several stages: hypothesis, experiment plan, evaluation of the results suitability for a particular task.
  6. .

  7. Communication. Presentation of data in the form of reports, on the basis of which proposals for solving a particular problem are built.
  8. Communication.

Any project has a chance for error or exception.

Sphere of application

Data science is actively applied in commercial and non-commercial organizations as well as for private use. The discipline is most often used in the following:

  • Demand forecasting. Based on past sales data, future demand can be forecasted. Regularities are determined, which allow you to quickly plan and restructure business processes.
  • .

  • Recommendations. Internet services use Data science to generate suggestions based on user preferences, such as music, videos, online shopping, etc.
  • Recommendations.

  • Pricing. Internet shopping companies have data on sales of the previous period. This information allows you to analyze the prices and form the best offer.

The volume of data is growing regularly. In this regard, Data science technologies are also rapidly developing, providing great opportunities for obtaining and processing data in various areas. Data science technologies are also rapidly developing, providing great opportunities for obtaining and processing data in various fields.

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