Select articles from Kavita’s knowledge bank
AI Strategy & The Business Side of AI
This article discusses what an AI strategy means, the different…
One of the questions that often comes up is what’s…
Word2Vec is a widely used word representation technique that uses…
Kavita Ganesan is an AI advisor, strategist, educator, and founder of Opinosis Analytics. She works with senior management teams across the enterprise to help them optimize their business with AI by discovering high-impact AI opportunities and providing a roadmap for implementation.
With over 15 years of experience, Kavita has scaled and delivered multiple successful AI initiatives for fortune 500 companies as well as smaller organizations. She has also helped leaders and practitioners around the world through her blog posts, coaching sessions, and open-source tools.
Kavita holds degrees from prestigious computer science programs, specifically a Masters degree from the University of Southern California, and a Ph.D. from the University of Illinois at Urbana Champaign, with a specialization in Applied Artificial Intelligence.
Kavita has been featured by numerous media outlets including Forbes, CEOWorld, CMSWire, Verizon, SDTimes, Techopedia, and Ted Magazine. To learn more about her frameworks and ideas, get her AI book for business leaders.
Work with Kavita
With over 15+ years of experience in the field, Kavita helps executives, business leaders, entrepreneurs, and innovators looking to incorporate AI and improve business outcomes. Here are two primary ways she helps:
Advisory & Consulting
If you’re struggling to find and assess AI opportunities, develop your AI strategy, or you’re unsure about the value of your deployed AI systems, Kavita can help bring clarity to strategy and implementation initiatives.
Training & Workshops
Kavita trains executives, mid-managers, innovators, and entrepreneurs on a variety of Business AI topics, giving them practical tools to be successful in the integration of AI, without confusing the audience with unnecessary technical jargon.
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Kavita’s select publications
Segmentation of clinical texts into logical groups is critical for all sorts of tasks such as medical coding for billing, auto drafting of discharge summaries, patient problem list generation, population…
This is a short study paper that categorizes positive and negative review sentences into 4 categories: positive only, praise, negative only and complaint. The intuition is that praise sentences and…