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Data Science

Our area of work - data science including data analysis, data mining, machine learning, neural networks, deep learning, artificial intelligence.

General skills

We do a full cycle of complex projects development: from problem formulation, data search, data collecting, data processing, data research and creating of machine learning models to deployment on production and supporting.

In our work we use various supervised and unsupervised machine learning methods, including classic algorithms (Linear Regression, Logistic Regression, SVM, K-means, KNN, Decision Trees, Gradient Boosting etc.) and Neural Networks and Deep Neural Networks (P, CNN, RNN, LSTM, AE etc.).

Supervised and unsupervised machine learning
Data collection
Exploratory data analysis
Online learning
Information retrieval
Feature selection and feature extraction
Data representations
Quality metrics
Dimensionality reduction
Time series processing
Data scaling and normalization
Classification task
Regression task
Learning to rank
Clustering
Outliers detection

Skills by fields of application

Image Processing
Image Processing
Natural language processing
Natural Language Processing
Recommendation systems
Recommendation Systems
Data Visualization
Data Visualization
Statistic research
Statistical Research and Predictions

Data Science Workflow

workflow scheme

Cases

  • Ismael Matsuura

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  • Lawanda Batchelder

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  • Bennett Arbogast

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  • Shanna Parcell

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  • Shanna Parcell

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  • Shanna Parcell

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  • Shanna Parcell

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