Stokastik

Machine Learning, AI and Programming

Tag: BiLSTM

Designing large scale similarity models using deep learning

Finding similar texts or images is a very common problem in machine learning used extensively for search and recommendation. Although the problem is very common and has high business value to some organisations, but still this has remained one of the most challenging problems when the database size is very large such as >50GB and we do not want to lose on precision and recall much by retrieving only 'approximately' […]

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BiLSTM-CRF Sequence Tagging for E-Commerce Attribute Extraction

In the last post we had used Conditional Random Fields (CRF) to extract attributes from e-commerce product titles and description. CRFs are linear models just like Logistic Regression. The drawback with linear models is that they do not take feature-feature interaction or higher order feature terms into account while building model. Linear models can under-fit on the data while too much non-linearity can lead to over-fitting.┬áNon-linear models such as Neural […]

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