Machine learning
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Machine learning

We create products based on artificial intelligence and optimize your business by finding dependencies in your data.

Workflow

1Data collection

We study the available data, collect new ones, organize data markup.

2Research

We study the data, come up with the first hypotheses, choose which models we will try.

3Learning

We search for a mathematical function that will precisely perform the specified task. In other words, we train neural networks or another algorithm.

4Evaluation

After the algorithm has shown itself well on training data, we evaluate its effectiveness on data that it has not encountered yet.

5Optimization

As a result, we optimize the model so that it works as quickly as possible during the inference.

6Inference

We create a high-load system for the model to work, integrate with the data source and give the result to consumers in the right form.

Machine learning is an algorithm for solving problems that were previously subject only to man. We will train a computer to see, hear and understand, or to find dependencies in such data where even a person could not figure it out. The essence of machine learning is that a computer analyzes a large amount of data and on its own finds dependencies in them. For example, if you show it a lot of photos of cats and dogs, and say where a cat is and where a dog is, the algorithm, seeing a new photo, can say what kind of animal is captured on it.

Machine learning is suitable for:

  • Solving computer vision problems, i.e. image processing;
  • Recognition of sounds and voices;
  • Chatbot development;
  • Work with text, for example, translation into other languages;
  • Analysis of user’s behavior in the application or on the website;
  • Churn (customer attrition) prediction;
  • Optimization of processes in manufactures;
  • And many other tasks.
  • Used technologies

    Python
    Tensorflow
    Scikit-learn
    Xgboost
    Keras
    Numpy
    PyTorch
    Catboost

    Order a machine learning project!

    Evaluated the capabilities of technology? Want to integrate machine learning into your project? Write to us!

    Our experience

    Практика

    Website and mobile application for navigating the UMN festival.

    Ural Music Night

    A tool for improving your skills in praktikal shooting.

    Alibra School

    Applications for learning foreign languages for the federal network of schools ALIBRA SCHOOL.

    FAQ

    Where does the labeled data come from?
    If you do not have any data, we will discuss with you how to collect it. We can also organize data labeling.
    How is data confidentiality ensured?
    If your data cannot be given to third parties, we can decide how to anonymize the data. Thus, it will be possible to learn from data that will not contain personal information.
    What can machine learning algorithms run on?
    Depending on the task, they can be launched both on a server, which can be deployed in the cloud or stored on your own, and on user devices, for example, phones.
    Everyone is talking about neural networks. How is this related to machine learning?
    Neural networks are a type of machine learning. By their operating principle, they resemble the structure of the brain and better than other approaches solve problems that do not have a clear structure in the data, for example, processing images, sounds, texts.

    Blog

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    May 21, 2020

    In this article, we will talk about typical problems in UX that are found in applications of both startups and large corporations.

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    April 14, 2020

    We organized a test task, built the process of preparing for lectures and homework assignments, transferred classes from offline to online.

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    Experience instead of money: how to (not) make money on a mobile application

    April 9, 2020

    The story of our client about the promotion of a mobile application for meditation.

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