Usage of of data science and computer science in business applications
In the modern world we accumulate more and more data every day. Everyone intuitively understands that the accumulation of data helps to identify some patterns and make decisions based on them. For example, shopping networks collect your data, data about your purchases and visits to stores to make personal bonus program. Fitness trackers collect data about your activity and movement. Cars know your preferences for the temperature in the cabin, the speed of traffic on different sections of the road and at different times of the day.
A lot of startups are born every day just from ideas what additional information and value can be extracted from data. For example, if you compare the heart rate, body temperature, calls from the phone and the speed of the car, you can determine when the driver received an unpleasant call and warn him to keep calm and drive carefully.
From the point of view of computer data processing, very large abount of data can not be processed with traditional algorithms. With large data we need a different approach - it is machine learning. In this case, the person gives the computer input data, determines the way the machine learns (determines the algorithms), but the machine learns "itself" and eventually gives out some solution. In order for the machine to be able to "solve" something and "learn" something, properly prepared data and correctly selected (in simple cases) or created mathematical models are needed.
In this process, two main roles are involved:
- Data scientist is a mathematician who chooses or develops algorithms to solve a specific problem and implements an algorithm in a prototype
- Developer who implements the created mathematical model in the form of production code.
Although this process is far from simple, there is no special magic in it. There are algorithmic frameworks and well-documented cloud services for speech recognition, pattern recognition, natural language recognition, classification of objects, etc., that operate according to the principles of machine learning and neural networks. Client can used them as a "black box", which simply solves the tasks.
Machine learning team Kiev, Ukraine
The development of machine learning is a promising direction for Evergreen, we will be happy to offer you the data science / machine learning services in Ukraine.
The tasks of computer science, that we offer to solve:
- Development of algorithms
- Expert systems
- Data structures and algorithms
- Big Data Tasks
- Data Mining
- Statistical analysis
- Cluster analysis
- Evolutionary and genetic algorithms
- Artificial neural networks
- Computer vision
- Pattern recognition
- Augmented Reality