https://github.com/ksm26/vector-databases-embeddings-applications
Unlock the power of vector databases with the "Vector Databases: from Embeddings to Applications" course! A journey that will equip you with essential skills to leverage vector databases for various applications.
https://github.com/ksm26/vector-databases-embeddings-applications
embeddings generative-ai hybrid-search image-recognition knn knn-classification machine-learning multilingual-search natural-language-processing rag recommender-system retrieval-augmented-generation semantic-search vector-database
Last synced: about 2 months ago
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Unlock the power of vector databases with the "Vector Databases: from Embeddings to Applications" course! A journey that will equip you with essential skills to leverage vector databases for various applications.
- Host: GitHub
- URL: https://github.com/ksm26/vector-databases-embeddings-applications
- Owner: ksm26
- Created: 2024-01-25T15:29:33.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-29T14:29:52.000Z (over 1 year ago)
- Last Synced: 2024-01-30T14:24:51.894Z (over 1 year ago)
- Topics: embeddings, generative-ai, hybrid-search, image-recognition, knn, knn-classification, machine-learning, multilingual-search, natural-language-processing, rag, recommender-system, retrieval-augmented-generation, semantic-search, vector-database
- Language: Jupyter Notebook
- Homepage: https://www.deeplearning.ai/short-courses/vector-databases-embeddings-applications/
- Size: 5.74 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🚀 [Vector Databases: from Embeddings to Applications](https://www.deeplearning.ai/short-courses/vector-databases-embeddings-applications/)
💻 Welcome to the "Vector Databases: from Embeddings to Applications" course! This course, instructed by Sebastian Witalec, Head of Developer Relations at Weaviate, will equip you with essential skills to leverage vector databases for various applications.
## Course Summary
In this course, you will delve into the world of vector databases and their applications. Here's what you can expect to learn and experience:
1. 📚 **Understanding Vector Databases**: Explore the role of vector databases in natural language processing, image recognition, recommender systems, and semantic search.
2. 🧠 **Embeddings and Similarity (L1)**: Learn how embeddings capture the meaning of data and how vector databases gauge the similarity between vectors.
3. :mag_right: **Demonstration of KNN (L2)**
4. :chart_with_upwards_trend: **Approximate nearest neighbours (L3)**
5. ⚙️ **Building RAG Applications (L6)**: Develop Retrieval Augmented Generation (RAG) applications using vector databases and LLMs.
## Key Points
- 🔑 Build practical applications, including hybrid and multilingual searches, for diverse industries.
- 🔍 Understand vector databases and their role in developing GenAI applications without the need to train or fine-tune an LLM yourself.
- 🤔 Learn to discern when it's best to apply a vector database to your application.
## About the Instructor
🌟 **Sebastian Witalec** is the Head of Developer Relations at Weaviate. With extensive knowledge in the field, Sebastian will guide you through the intricacies of vector databases.
🔗 To enroll in the course or for further information, visit [deeplearning.ai](https://www.deeplearning.ai/).