Webinar

How to Build a Sentiment Analysis App with Hugging Face

Madhukar Kumar - <p><span style='font-size: 11pt;'>Chief Developer Evangelist at SingleStore</span></p>
Pranav Aurora - <p><span style='font-size: 11pt;'>Product Manager at SingleStore</span></p>

overviewOverview

Join us for our exciting upcoming webinar titled "How to Build a Sentiment Analysis with Hugging Face" where we showcase the practical application of AI in use cases that require analysis of text from multiple documents, data types, or data stores. Our technical experts will guide participants through the realms of sentiment analysis, semantic search, and data vectorization, and their potential to optimize and upgrade traditional business processes. 

You'll get hands-on experience building your own sentiment analysis model using the renowned Hugging Face platform, with real-time coding and demonstrations. The webinar will also delve into the concept of semantic search and demonstrate how to vectorize data into SingleStoreDB for intelligent and context-rich results. This enlightening session is a must-attend for software engineers, data scientists, AI enthusiasts, and anyone interested in harnessing the power of AI for organizational development.

What You'll Learn:

  • Understand the concept of semantic search, sentiment analysis and their value in AI applications.

  • Learn how to build an open source AI application on private data using the Hugging Face platform.

  • Explore how to vectorize data into SingleStoreDB for more contextualized and intelligent results.

  • Gain insights into applying AI and ML technologies for HR, Advertising, Consulting and myriad business processes.

  • Participate in a hands-on demo and real-time code sharing session, enhancing your practical understanding of the subject.



  • Madhukar Kumar, Chief Developer Evangelist at SingleStore
  • Pranav Aurora, Product Manager at SingleStore

Madhukar Kumar

Chief Developer Evangelist at SingleStore

Pranav Aurora

Product Manager at SingleStore

Event Details


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Duration

60 minutes

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Watch Now

On-Demand