Data Science

Data Science

Data Science

Nowadays data science can generate business value from data analysis.
Data analysis field involves such operations as scrapping the data, its processing and providing useful conclusions and visualization. Using data analysis techniques it possible to figure out which feature influences the most on the product price, predict currency value, build the recommendation engine, detect and predict fraud incidents etc. Having your data or obtaining public information, many useful, unexpected and profitable results can be collected.
To turn them into business assets we combine data science methods with corresponding IT tools and frameworks.

1COMPUTER VISION

We perform objects detection, tracking and recognition using high performance video and image processing.

Separately we have experience with:

  • people detection and tracking
  • faces, poses, gesture recognition
  • drone and satellite data processing
  • text recognition for passports, structured documents, car license plates, signboards, bills, etc.
  • analytics collection.

We use machine learning methods with CNN (TensorFlow, Yolo, ImageNet) as well as  specific frameworks like OpenCV, OpenFace to achieve optimal quality and performance.

2TEXT ANALYTICS

We use modern technologies for text operating in a human like manner, giving the opportunity to generate and analyze text concerning the key words, text sentiment, emotion, structure, etc.

They used for following business tasks solving:

  • corporate search engines building
  • articles classification
  • documents relevancy definition.

We use Scikit-Learn, NLTK, ElasticSearch, gensim.

3PREDICTIVE ANALYTICS

Predictive analytics allows to utilize all the current and historical facts to produce predictions about future events. the application built with predictive analytics techniques can provide with probability of different decision profit, which is state of the art approach in nowadays time of making big amount of immediate decisions.
We have experience with prediction of:

  • currency rate
  • clients churn
  • fraud
  • customer attrition
  • sales amount.

We use Scikit-Learn, NumPy, Pandas, XGBoost and other  technologies.


Projects