Tips for Buying AI Solutions Wisely

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85% of global executives believe that AI can become their competitive advantage. So, the rush to AI adoption is understandable. Unfortunately, implementing AI from scratch takes time, and success comes with experience in building and deploying solutions.

To speed things up, “buying” instead of building from scratch seems like a…

I have spent much of my career as a graduate student researcher, and now as a Data Scientist in the industry. …

A Gensim Word2Vec Tutorial

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The idea behind Word2Vec is pretty simple. We’re making an assumption that the meaning of a word can be inferred by the company it keeps. This is analogous to the saying, “show me your friends, and I’ll tell who you are.

If you have two words that have very similar…

Prevent CSR burnout and improve customer service workflows with AI

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Got customer service data?

Customer service inquiries come in all shapes and forms. Emails, support tickets, tweets, chat conversations with support staff, and chatbot conversations. That’s a lot of data that you’re dealing with. …

Do this one thing to improve your chances of ML success

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Have you seen machine learning solutions fall flat in practice?

Well, I have. Several times. I get occasional panic calls from teams about their 98% accurate models generating questionable predictions once released to actual users.

Did they build a…

Back in 2006, when I had to use TF-IDF for keyword extraction in Java, I ended up writing all of the code from scratch. Neither Data Science nor GitHub were a thing back then and libraries were just limited.

The world is much different today. You have several libraries and…

Based on some recent conversations, I realized that text preprocessing is a severely overlooked topic. A few people I spoke to mentioned inconsistent results from their NLP applications only to realize that they were not preprocessing their text or were using the wrong kind of text preprocessing for their project.

word_cloud python library

About a year ago, I looked high and low for a Python word cloud library that I could use from within my Jupyter notebook. I needed it to be flexible enough to use counts or tfidf when needed or just accept a set of words and corresponding weights.

I was…

ROUGE stands for Recall-Oriented Understudy for Gisting Evaluation. It is essentially a set of metrics for evaluating automatic summarization of texts as well as machine translations.

It works by comparing an automatically produced summary or translation against a set of reference summaries (typically human-produced). …

The probability of an n-gram or word tells you how important a word is to a document. Unfortunately, since a document almost always has important words inter-mingled with conjunctions and determiners and other types of noise, using the raw probabilities may not be a good idea. One thing that you…

Kavita Ganesan

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