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Web, Mobile, QA, Embedded


Real Estate


Java, JavaScript, Python, Swift, Junit, Amazon, Caffe, Kaldi

Project type


Overview: works in ​area​ of machine learning of industrial visual information for construction companies. This solution allows the user to inspect, track progress, and improve field documentation by analyzing images and video of construction areas.

Business needs:

Create the process of testing using machine learning methods for video and audio inputs.

Create test procedures and validation/verification for web part and UI testing.

Test integration solution for video and images services.

Provide mobile iOS App testing and its integration into the overall system.

Suggested solutions from Svitla:

Build integration test procedures for different components of product.

Build dataset for test cases for learning processes for machine learning based on Caffe and Kaldi.

Create pre-production models for system validation.

Create automation process with Selenium and Jasmine on front-end.

Value delivered

Production level of the machine learning system with stable validation and verification process.
Increased stability of product by full cycle of functional testing.
Better machine learning results for real users on video and images.
Saved time resources with effective automation testing bench which reduced portions of manual testing.

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