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LinkedIn – Vector, Graph, and DynamoDB 2024-7

LinkedIn – Vector, Graph, and DynamoDB 2024-7

Published on: 2024-08-23 13:18:16

Categories: 28

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Description

Vector Graph and DynamoDB course. In this course, MLOps expert Noah Gift explores vector and graph databases. These powerful tools are very useful for managing and extracting insights from large and complex data sets. Due to the continuous growth of data volume, scalability is of great importance. We will learn how vector and graph databases can efficiently store data while maintaining relationships between them, thereby enabling more advanced analysis. Using real-world examples, you’ll see how these databases provide scalability for machine learning, fraud detection, social networking, and more.

In today’s world, data is recognized as the most valuable asset of organizations. However, managing and analyzing huge amounts of data poses great challenges. Traditional databases may not be sufficient to deal with the complexity and scale of today’s data. Vector and graph databases provide an innovative solution to these challenges by providing new approaches to data storage and management. Vector databases store data as numeric vectors. This enables mathematical operations to be performed on the data and allows machine learning models to effectively analyze the data. On the other hand, graph databases display the relationships between data in the form of graphs. This structure enables complex data modeling and the discovery of hidden patterns. In this course, you will learn the basics of vector and graph databases and learn how to use them in different scenarios. You’ll also work with DynamoDB, one of the most popular NoSQL databases, as a hands-on example.

What you will learn:

This course is suitable for people who:

Course details

Course headings

Vector Graph and DynamoDB

Course images

Vector Graph and DynamoDB

Sample video of the course

Installation guide

After Extract, view with your favorite Player.

Subtitle: English

Quality: 720p

download link

Download file – 162 MB

File(s) password: www.downloadly.ir

File size

162 MB

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