Engines

Abstract Imputation fixes broken data. Methods are from making it constant mean to clustering, regression and generative networks. What if...

Introduction Oftentimes before we get to develop the Machine Learning Solution for Extracting Information, we need to test several approaches...

Motivation why we choose points of interest (POI) Maps Services, like those in Google and Bing, usually provide us with...

Introduction challenge of Classifying SpaCy’s ORG Named Entities with Statistical Text Analysis Recently, we were tagging a lot of texts...

Problem Statement in Related Organizations Addresses with Web-Search, spaCy, and RegExes.  Recently, one of our clients has contacted us with...

Active Learning is a semi-supervised technique that allows labeling less data by selecting the most important samples from the learning process (loss) standpoint. It can have a huge impact on the project cost in the case when the amount of data is large and the labeling rate is high. For example, object detection and NLP-NER problems.The article is based on the following code: Active Learning on MNIST (more…)

Subject: Automated Document Classification, Document Capturing, Data Extraction, AI Document RecognitionBusiness Areas: Banking, FinTech, RetailData Science Areas: Computer Vision, Machine...

Subject: Automated Document Classification with Machine Learning, Data extraction, Document ClassificationData Science areas: Natural Language Processing, Computer vision, Optical Character...

Subject: Price Prediction System, Prediction Accuracy Evaluation, Deep LearningData Science areas: Feature Analysis, Estimators, Machine LearningArchitectures: Linear Regression, Boosting Regressors,...