Welcome! I’m Kavita Ganesan. I’m an AI Consultant, Speaker and Educator.
I use my blog as a platform to teach and share ideas. Some of my articles have helped readers around the world, and I hope it helps you too!
Visit my about page to learn more.
Recent Blog Posts
Word2Vec: A Comparison Between CBOW, SkipGram & SkipGramSI
Word2Vec is a widely used word representation technique that uses neural networks under the hood. The resulting word representation or…
HashingVectorizer vs. CountVectorizer
Previously, we learned how to use CountVectorizer for text processing. In place of CountVectorizer, you also have the option of…
Text Classification: Best Practices for Real World Applications
Most text classification examples that you see on the Web or in books focus on demonstrating techniques. This will help…
How to Improve Productivity in Customer Support with A.I.?
Companies receive support enquiries from various channels. This may include emails, support tickets, tweets, chat conversations with customer support representatives…
10+ Examples for Using CountVectorizer
Scikit-learn’s CountVectorizer is used to transform a corpora of text to a vector of term / token counts. It also…
Build Your First Text Classifier in Python with Logistic Regression
Text classification is the automatic process of predicting one or more categories given a piece of text. For example, predicting…
Reader’s Thoughts
I just read your article ‘All you need to know about text preprocessing for NLP and Machine Learning’ on KDnuggets and I have to say it is one the best, most comprehensive and well-explained articles I’ve ever encountered related to pre-processing.
I arrived at your profile after going through your articles.They are a treasure trove of knowledge and really help me understand many of the topics prevalent in the field and industry.
I came across your blog and git account while reading online on sentiment analysis. I really liked the resources that you have shared and I wanted to thank you for these because I am doing my first Sentiment Analysis project by referring to these.
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