Jan 16
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Dive deep into the world of vector embeddings with this comprehensive guide! We'll demystify how these numerical representations of text and data unlock powerful applications like Semantic Search, Classification and Clustering. What you'll Learn: 1. What are vector embeddings? An easy-to-understand explanation of the core concept. 2. How do embeddings enable semantic analysis? Discover how we can quantify the meaning and relationships between words, phrases and sentences. 3. Introduction to Gemini Embedding Models: Get to know Google's cutting-edge models for generating high-quality embeddings. 4. Practical Use Cases: We'll walk through real-world applications like building a semantic search engine. 5. Hands-on Demo: A step-by-step tutorial on how to use the Gemini API to create your own embeddings. Codebase: https://github.com/SauravP97/AI-Engineering-101/tree/main/vector-embeddings Research Paper link: https://arxiv.org/pdf/2503.07891 My Socials š šāāļø Linkedin: https://www.linkedin.com/in/saurav-prateek-7b2096140/ āļø Instagram: https://www.instagram.com/saurav_prateek/ ā”ļø Book a 1:1 session with me for Interview Preparation and Career guidance, Mock Interviews and Resume Review on Topmate: https://topmate.io/saurav_prateek