Master Vector Database - Chromadb

ChromaDB methods, collections, query filter, langchain, RAG, semantic search and much more.

What you'll learn

Learn integration Vector databases with LangChain, Open AI

Master Embeddings

Transformer Models for vector embedding, Generative AI, Open AI API Usage

Understand the fundamentals of vector databases and their role in AI, generative AI, and LLM (Language Model Models)

Implement code along exercises to build and optimize vector indexing systems for real-world applications

Requirements

Basic Python programming knowledge

Desire to learn and excel more

Description

Welcome to the Master Vector Database course - ChromaDB!Are you ready to unlock the power of ChromaDB and take your data handling skills to the next level? Look no further! This course is designed to equip you with all the tools and techniques you need to become a master of vector databases.In this course, you'll dive into the fascinating world of ChromaDB, starting with an introduction that will lay the foundation for your journey. From there, you'll learn various methods on how to efficiently manage collections and add document-associated embeddings.But that's just the beginning! Ever struggled with querying data effectively? Not anymore! We'll teach you how to query data with precision using filters like 'where' and even delve into querying multiple documents using the powerful Langchain + ChromaDB combination.And it doesn't stop there! Get ready to explore advanced topics such as storing and querying stock companies data, semantic search using duckdb+parquet, and even mastering multimodal image embedding search techniques.But wait, there's more! Ever wanted to perform local vector database searches seamlessly? We'll show you how it's done using the dynamic trio of ChromaDB, Langchain, and OpenAI.And that's not all! Brace yourself for an exciting exploration into the world of RAG with ChromaDB and OpenAI/GPT Model integration, as well as leveraging ChromaDB with Gemini Pro embedding model.So, if you're ready to elevate your skills, expand your knowledge, and become a true expert in vector databases, then this course is tailor-made for you. Don't miss out on this incredible opportunity to become a master of ChromaDB. Enroll now and let's embark on this exhilarating journey together!

Overview

Section 1: Introduction

Lecture 1 Introduction to Vector Database

Lecture 2 Vectors and Embeddings

Lecture 3 Explain Vector Database like I'm 5

Section 2: ChromaDB

Lecture 4 Introduction to ChromaDB

Lecture 5 Methods on collections

Lecture 6 Storing "The Matrix" collections

Lecture 7 Adding document associated embeddings

Lecture 8 Query data with 'where' filter

Section 3: Query multiple documents - ChromaDB + Langchain

Lecture 9 ChromaDB + Langchain - QA on multiple documents - Part 1

Lecture 10 ChromaDB + Langchain - QA on multiple documents - Part 2

Section 4: Store and Query Stock Companies Data

Lecture 11 setup database, and getting data from wikipedia

Lecture 12 query stock companies data with filters

Section 5: Semantic Search, Duckdb+parquet with ChromaDB

Lecture 13 Storing Knowledgebase information with Duckdb+parquet

Lecture 14 Running semantic searches with filters, use different embedding model

Section 6: Multimodal image embedding search

Lecture 15 setup environment, data, chromadb database

Lecture 16 Image search using embedding model

Lecture 17 Finding items within an image using model

Lecture 18 Using metadatas to enhance your queries

Section 7: Local Vector Database with ChromaDB + langChain + OpenAI

Lecture 19 Query FED Speech data with local vectorDB, OpenAI and Langchain

Section 8: Streamlit + ChromaDB + LangChain - Summarize any document

Lecture 20 ChromaDB + Langchain to summarize a PDF document - Part 1

Section 9: RAG with ChromaDB and OpenAI/GPT model

Lecture 21 RAG on wikipedia articles using GPT 3.5 model

Section 10: ChromaDB with Gemini Pro embedding model

Lecture 22 Using Gemini Pro embedding model for chromaDB

Section 11: Congratulations and Thank You!

Lecture 23 Your feedback is very valuable!

Anyone who want to explore the world of AI and Vector Database,Anyone who want to step into Vector Database world with practical learning,Data engineers, database administrators and data professionals curious about the emerging field of vector databases,Software developers interested in integrating vector databases into their applications.