Manas Ranjan Kar
  • Male
  • Gurgaon
  • India
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Profile Information

Short Bio:
I am an analytics professional helping clients making sense of their data and build a powerful case for business change using analytics in their respective companies. I have worked on a variety of problems in the areas of natural language processing & predictive analytics. I have delivered multiple talks at IIM Lucknow on using text analytics for deep insights into customer's opinions.

As an avid Kaggler, I like to work on generating new ideas and devising feasible solutions to broadly relevant problems.

My specialties include:

Natural Language Processing (NLP)
Machine Learning for Text Analytics
Text Analytics Tools ( Gephi, VOSViewer, GATE)
Retail Analytics
Predictive Analytics
Data Visualization
Customer Insights
Data Architecture
Thought Leadership
BI/Analytics Tools (Tableau, Axure)
Statistical Tools/Programming (Python, SPSS)
Juxt Smart Mandate
Executive Management
Text Analytics & Natural Language Processing
LinkedIn Profile:
Networking, New venture, Recruiting, Other

Manas Ranjan Kar's Blog

Impactful text analytics for smarter businesses

Posted on December 28, 2015 at 7:57am 0 Comments


Service is great, but the desserts are bad”. Overall rating 4.5/5.

Many times we have gone into a restaurant alone or in a group, came out happy and still rated it a 3 or a 4 on social media. Does any one check why 2 precious points were deducted? No one will read your review unless the overall rating dips below 3.5. Is it an healthy practice? Of course not.

Frankly, no one is to blame except the rating scales and NPS…


Using GloVe vectors in Gensim

Posted on December 28, 2015 at 7:53am 0 Comments

Natural Language Processing (NLP) is a messy and difficult affair to handle. Preprocessing, machine learning, relationships, entities, ontologies and what not.

Word embeddings/representations – ever since they came in with great work of Mikolov et al, they have been revolutionary to say the least. The concept itself is very intuitive and motivates deeper understanding fora wide range of applications. The…


Can Context Extraction replace Sentiment Analysis?

Posted on September 7, 2015 at 12:24am 4 Comments

Sentiment analysis is hard. Most of the systems on the market will clock anywhere around 55-65% for unseen data, even though they might be 85%+ accurate in their cross-validations.

A couple of reasons why creating a generic sentiment analyser is tough;

- There is too much variation in texts across domains, leading to different meanings

- Identifying sarcasm and combination of phrases like, 'not bad' is not equal to 'not' AND 'bad'

At this…


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