At ParallelDots, we pay special attention to the customers’ feedback to build features that work best for them. Recently we’ve been getting a number of […] Read More
Category: Data Science
“What we want is a machine that can learn from experience“ Alan Turing There is no doubt that Machine Learning has become one of the […] Read More
Data science is an inter-disciplinary field which contains methods and techniques from fields like statistics, machine learning, Bayesian etc. They all aim to generate specific […] Read More
“The thinking in AI has changed from ‘What’s possible?’ to ‘How do I do this?’” explains Rafiq Ajani at McKinsey educational AI forum. Natural Language […] Read More
Sentiment Analysis, in the simplest words, is determining whether a piece of text is positive, negative, or neutral. The system combines natural language processing and […] Read More
Named Entity Recognition (NER) is a particularly interesting branch of Natural Language Processing (NLP) and a subpart of Information Retrieval (IR). A NER model is […] Read More
ParallelDots has distinguished itself based on its innovation stemming from its rich research centric environment. At ParallelDots the mantra is not merely ‘getting the job […] Read More
How do you measure your customers’ happiness? What’s the first metric that pops into your mind? If your answer was Net Promoter Score (or NPS), […] Read More
An untrained statistical model is like a Ferrari that simply will not run. In other words, it is simply not of much use. Supervised Learning […] Read More
Word embeddings are basically a form of word representation that bridges the human understanding of language to that of a machine. Word embeddings are distributed […] Read More
