Machine Intelligence LaboratoryOCR-decisions testing system by MIL TeamPoint out the main drawbacks of the existing OCR-decisions testing system and propose our own algorithm.Apr 13, 2021Apr 13, 2021
Machine Intelligence LaboratoryModels, bugs & how can we discover them?In this tutorial, we are going to share the insights about quick and effective detection of bugs in the ML models' performance.Apr 8, 2021Apr 8, 2021
Machine Intelligence LaboratoryBeing outside: 5 reasons to launch the project with the external R&D teamIn this article, we discuss 5 main factors of making a decision about working with an external outsourced team.Feb 16, 2021Feb 16, 2021
Machine Intelligence LaboratoryRelative regularization coefficients: ARTM & TopicNet usingBy reading this tutorial you will know how to use TopicNet and ARTM libraries for building topic models with regularizers.Jan 22, 2021Jan 22, 2021
Machine Intelligence LaboratoryDivide and conquer: research and applied projects in MILWhy did we decide to separate our two main work directions: Applied AI & Research AI?Dec 20, 2020Dec 20, 2020
Machine Intelligence LaboratoryThe Magic of Denoise: subjective methods of audio quality evaluationSubjective methods evaluation of denoise models performance: advantages over algorithmic ones & two main metrics.Dec 11, 2020Dec 11, 2020
