Master Vector Databases

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Adnan Waheed

7:11:32

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1. Introduction

1. Introduction to Vector Database.mp4

15:19

2. Vectors and Embeddings.mp4

09:58

3. Explain vector database like Im 5.mp4

04:56

4. How vector database store data.mp4

06:36

5. How do vector database works.mp4

05:14

6. Vectors in 2D.mp4

07:44

2. The power of embeddings

1.1 vd vector embedding openai.zip

1. Create embeddings using OpenAI.mp4

11:03

2. Sentence Embedding Models.html

3. Using SQLite as vector storage

1. Setup and basic operations.mp4

09:23

2.1 vd sqlite vector search.zip

2. Creating, storing and retrieving vector data.mp4

19:35

3. Finding nearest vector.mp4

06:21

4.1 vd sqlite vss.zip

4. Vector search using sqlite-vss extension.mp4

15:11

4. ChromaDB

1. Introduction to ChromaDB.mp4

15:07

2. Revolutionizing the Data access with Vector Database.html

3.1 vector database chromadb.zip

3. Methods on collections.mp4

08:08

4.1 vector database chromadb the matrix .zip

4. Storing The Matrix collections.mp4

12:59

5. Adding document associated embeddings.mp4

10:59

6. Query data with where filter.mp4

09:44

7.1 vd chromadb + langchain qa multiple documents.zip

7. ChromaDB + Langchain - QA on multiple documents - Part 1.mp4

16:27

8. ChromaDB + Langchain - QA on multiple documents - Part 2.mp4

10:06

5. Facebook AI Similarity Search (FAISS)

1. Introduction to FAISS.mp4

16:13

2. Using similarity search for nearest neighbours.mp4

07:33

6. Pinecone

1. Introduction to Pinecone.mp4

19:24

2. Setup account, create an index, dashboard review.mp4

14:45

3. Understanding index creation configuration.mp4

09:00

4. Index management.mp4

15:44

5. Insert vector data to an index.mp4

15:26

6. Query vector data.mp4

12:06

7. Upsert vector data in batches.mp4

13:41

8. Upsert batches in parallel.mp4

01:52

9. Upsert with metadata.html

10. Vector IDs must be string.mp4

06:51

11. Sentence transformer embeddings.mp4

09:45

12. Semantic search with metadata filtering - news articles.mp4

32:38

7. Qdrant

1. Introduction to Qdrant vector database.mp4

10:46

2. Connect with APIs.mp4

08:38

3. Create a qdrant python client.mp4

05:24

4. Create a collection.mp4

07:25

5. Create a vector store.mp4

05:10

6. Add document to vector store on the cloud.mp4

14:43

7. Query the document.mp4

09:38

8. Create a streamlit QA app.html

8. Congratulations and Thank You!

1. Your feedback is very valuable!.html

Description

Master Vector Database using Python, Embeddings, Pinecone, ChromaDB, Facebook FAISS, Qdrant, LangChain, Open AI

What You'll Learn?

Master Vector Database, Embeddings, ChromaDB, FAISS, Qdrant and much more
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.

Who is this for?

Anyone who want to explore the world of AI

Anyone who want to step into AI 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.

What You Need to Know?

Basic python knowledge

More details

Description
Are you ready to ride the next wave in the realm of data management?

Introducing our groundbreaking course: Vector Database Mastery. In this comprehensive program, we delve deep into the fascinating world of Vector Databases, equipping you with the skills and knowledge needed to navigate the data landscape of the future.

Why Vector Databases? Traditional databases are evolving, and the next generation is here â€“ Vector Databases. They are not just databases; they are engines of understanding. Harness the power of vectors to represent and comprehend complex data structures, bringing unprecedented efficiency and flexibility to your data management endeavors.

Course Highlights:
Foundations of Vectors: Dive into the basics of vectors, understanding their role as powerful mathematical entities in representing and manipulating data. Uncover the fundamental concepts that form the backbone of Vector Databases.
Embeddings Techniques: Master the art of embeddings â€“ the key to transforming data into a high-dimensional vector space. Explore techniques like Word Embeddings, Doc2Vec, and more, unleashing the potential to encode complex information into compact, meaningful vectors.
SQLite as a Vector Database: Witness the fusion of traditional SQL databases with the dynamic capabilities of vectors. Learn how to leverage SQLite as a Vector Database, enabling you to handle intricate relationships and queries with ease.
ChromaDB: Explore the cutting-edge ChromaDB, a revolutionary Vector Database that takes data representation to a whole new level. Delve into its architecture, functionalities, and real-world applications, paving the way for a new era of data management.
Pinecone DB: Step-by-step walkthrough about creating an index, prepare data, creating embeddings, adding data to index, making queries, queries with metadata filters and much more.
Qdrant Vector Database: Uncover the capabilities of Qdrant, a high-performance, open-source Vector Database designed for scalability and speed. Learn to implement and optimize Qdrant for various use cases, propelling your projects to new heights.
Langchain for QA Applications: Revolutionize question-answering applications using Langchain. Integrate vector-based search techniques into your projects, enhancing the precision and relevance of your results.
OpenAI Embeddings: Harness the power of OpenAI embeddings to elevate your natural language processing projects. Learn to integrate state-of-the-art language models into your applications, pushing the boundaries of what's possible in text-based data analysis.
Join the Vector Revolution!
Enroll now to future-proof your data management skills. The Vector Database Mastery course is not just a learning experience; it's your ticket to staying ahead in the rapidly evolving world of data.

Don't miss out on the next wave â€“ secure your spot today and become a master of Vector Databases!
Who this course is for:
Anyone who want to explore the world of AI
Anyone who want to step into AI 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.

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Hello Everyone, I am an entrepreneur, a deliverer, a dreamer, a believer, a darer and a doer. I had worked in Bloomberg for 17 years, and build, manage, and lead several projects and team on global basis. After Bloomberg, had build my own companies like KlickAnalytics, ClickAPIs, ZoomMarkets providing global financial markets analytics with tera bytes data on cloud servers.I've worked extensively with PHP, Python, Angular, Rest APIs, Cloud systems, time series database, financial data analytics, UNIX systems, MongoDB, PostgreSQL, and advanced system architecture design and more.My utmost passion is the invention, innovation, changing paradigms, game-changing disruptions, people, personal development and the true adventures of life. Master the getting the job done well.My Motto: Change the Game!

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