Vespa AI Search Engine and Vector Database with Python

Vespa AI Search Engine and Vector Database with Python, available at $84.99, with 25 lectures.

You will learn about Understand Vespa AI: Learn the fundamentals of Vespa AI to build and deploy powerful search engines and vector databases effectively. Build Search Applications: Create advanced search applications with Vespa AI using Python, focusing on real-time data processing and retrieval. Develop Vector Databases: Learn to develop, deploy, and manage vector databases with Vespa AI, enhancing search with machine learning models. Integrate Vespa AI with Python: Gain practical skills to integrate Vespa AI into Python projects, from deploying applications to scaling for real-world use case This course is ideal for individuals who are This course is designed for data scientists, software developers, and AI enthusiasts who want to build advanced search engines and vector databases using Vespa AI and Python. It's also ideal for anyone looking to enhance their skills in search technologies and machine learning integration. It is particularly useful for This course is designed for data scientists, software developers, and AI enthusiasts who want to build advanced search engines and vector databases using Vespa AI and Python. It's also ideal for anyone looking to enhance their skills in search technologies and machine learning integration.

Enroll now: Vespa AI Search Engine and Vector Database with Python

Summary

Title: Vespa AI Search Engine and Vector Database with Python

Price: $84.99

Number of Lectures: 25

Number of Published Lectures: 25

Number of Curriculum Items: 25

Number of Published Curriculum Objects: 25

Original Price: ₹799

Quality Status: approved

Status: Live

What You Will Learn

Understand Vespa AI: Learn the fundamentals of Vespa AI to build and deploy powerful search engines and vector databases effectively.
Build Search Applications: Create advanced search applications with Vespa AI using Python, focusing on real-time data processing and retrieval.
Develop Vector Databases: Learn to develop, deploy, and manage vector databases with Vespa AI, enhancing search with machine learning models.
Integrate Vespa AI with Python: Gain practical skills to integrate Vespa AI into Python projects, from deploying applications to scaling for real-world use case

Who Should Attend

This course is designed for data scientists, software developers, and AI enthusiasts who want to build advanced search engines and vector databases using Vespa AI and Python. It's also ideal for anyone looking to enhance their skills in search technologies and machine learning integration.

Target Audiences

This course is designed for data scientists, software developers, and AI enthusiasts who want to build advanced search engines and vector databases using Vespa AI and Python. It's also ideal for anyone looking to enhance their skills in search technologies and machine learning integration.

This course is a comprehensive guide to building advanced search engines and vector databases using Vespa AI and Python. It is designed for data scientists, software developers, AI enthusiasts, and anyone interested in mastering modern search technologies. Throughout this course, you will learn the fundamentals of Vespa AI, including its architecture and core components, and how to leverage its capabilities to build high-performance search applications.

You will gain hands-on experience with Python to integrate Vespa AI for real-time data processing, ranking, and retrieval. The course covers essential topics such as developing and deploying vector databases, creating scalable search engines, and using machine learning models to enhance search results. Additionally, you will explore advanced search techniques like semantic search, approximate nearest neighbor search, and hybrid search methods.

The course includes practical projects that guide you through deploying applications on Vespa Cloud, optimizing search performance with custom ranking functions, and implementing filters and cross-hit normalization for better search accuracy. By the end of this course, you will have the skills to create and deploy powerful, scalable search applications and vector databases.

Prerequisites include a basic understanding of Python and familiarity with Google Colab. This course provides valuable insights and practical experience to advance your knowledge in search technologies and AI integration.

Source code is provided in sections.

Course Curriculum

Chapter 1: Vespa Introduction

Lecture 1: What is Vespa?

Lecture 2: Key Features of Vespa

Chapter 2: Vespa's Overview and Architecture

Lecture 1: Low Level Overview of Vespa

Lecture 2: Architecture of Vespa

Chapter 3: Vespa Cloud and Tenant

Lecture 1: What is Tenant?

Lecture 2: Login to Vespa Cloud and Create Tenant

Lecture 3: Vespa Cloud Overview

Chapter 4: Install and Load Dependencies | Google Colab | Python

Lecture 1: Install pyvespa, vespacli, datasets

Lecture 2: Load Dependencies

Chapter 5: Dataset and Convert to Vespa's Format | Google Colab | Python

Lecture 1: Introduction to Dataset

Lecture 2: Load Dataset

Lecture 3: Convert Dataset to Vespa's Format

Chapter 6: Application Package and Vespa Cloud Instance | Google Colab | Python

Lecture 1: Create Application Package

Lecture 2: Method 1 : Create Vespa Cloud Instance using Interactively

Lecture 3: Method 2 : Create Vespa Cloud Instance using PEM File(Automatically)

Chapter 7: Deployment, Feed Data to Vespa Application | Google Colab | Python

Lecture 1: Deployment of Vespa Application

Lecture 2: Feed Data to Vespa Application

Lecture 3: Display Function to Pretty Display Result as DataFrame

Chapter 8: All Search Options in Vespa | Google Colab | Python

Lecture 1: Plain Keyboard Search

Lecture 2: Plain Semantic Search

Lecture 3: Hybrid Search with OR Query Operator

Lecture 4: Hybrid Search with RANK Query Operator

Lecture 5: Hybrid Search with Filter

Chapter 9: Document Operations | Google Colab | Python

Lecture 1: Update Content of Deployed Application

Chapter 10: Reconnect with Vespa Application | Google Colab | Python

Lecture 1: Reconnect with Vespa Application using PEM Files

Instructors

Kishan Tongrao
Sr Data Scientist

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Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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