Vector Databases Deep Dive: Mastering the Next Generation of Data Storage with Vector Databases

Babajide Ogunjobi

€59.99

Video Nov 2024 2hrs 2mins 1st Edition

Babajide Ogunjobi

€59.99

Video Nov 2024 2hrs 2mins 1st Edition

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

View table of contents

Key benefits

In-depth vector database fundamentals, indexing, and search methods
Hands-on demos with top platforms
Future-focused insights for practical, real-world applications

Description

Explore the dynamic world of vector databases, where modern data storage meets high-dimensional data management. This course begins by introducing the foundations of vector databases, explaining their purpose and how they differ from traditional databases. You'll uncover the reasons behind their growing popularity, diving into essential concepts like vectors, embeddings, and the complexities of high-dimensional data. Moving forward, the course covers advanced topics in search similarity and nearest neighbor algorithms, providing insight into efficient data retrieval in vector databases. You’ll also examine various indexing strategies—including flat indexing, HNSW, and product quantization—enhanced by real-world illustrations that bring abstract concepts to life. This knowledge will enable you to choose the best indexing method for your needs. Finally, you’ll apply these skills with hands-on introductions to leading platforms like Pinecone and Milvus, supported by practical demos. Closing with a forward-looking perspective, the course equips you with the expertise to navigate the evolving landscape of vector databases and implement them effectively in real-world scenarios.

Who is this book for?

This course is ideal for data scientists, machine learning engineers, and database administrators looking to specialize in vector databases. A basic understanding of traditional databases and familiarity with vectors or embeddings is recommended, though the course provides a thorough introduction to key concepts.