Quest 1 - Foundations of Vector Databases

By the end of this quest, you will be able to:

• Explain the core concepts of vector databases and how they differ from traditional databases.
• Understand the role of vector embeddings and why they are essential for handling high-dimensional data.
• Describe the architecture and key features of ChromaDB, including its use cases and advantages.
• Identify various real-world applications of vector databases, such as image search, recommendation systems, and text similarity analysis.
• Lay the groundwork for practical implementations by gaining a strong theoretical understanding of how vector databases process and retrieve data.