Master Vector Database With Python For Ai & Llm Use Cases
Last updated 6/2024
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Learn Vector Database using Python, Pinecone, LangChain, Open AI, Hugging Face and build out AI, ML , Chat applications
What you’ll learn
Pinecone Vector Database, LangChain, Transformer Models for vector embedding, Generative AI, Open AI API Usage, Hugging Face Models
Master the essential techniques for vector data embedding, indexing, and retrieval.
A Practical Code Along with Semantic Search Use Case in Detail with Named Entity Recognition
Developing an AI Chat Bot for Cognitive Search on Private Data Using LangChain
Understand the fundamentals of vector databases and their role in AI, generative AI, and LLM (Language Model Models).
Learn how vector databases enhance AI workflows by enabling efficient similarity search and nearest neighbor retrieval.
Gain practical knowledge on integrating vector databases with Python, utilizing popular libraries like NumPy, Pandas, and scikit-learn.
Implement code along exercises to build and optimize vector indexing systems for real-world applications.
Explore practical use cases of vector databases in AI, generative AI, and LLM, such as recommendation systems, content generation, and language translation.
Understand how vector databases can handle large-scale datasets and support real-time inference.
Gain insights into performance optimization techniques, scalability considerations, and best practices for vector database implementation.
Requirements
Basic understanding of programming concepts and experience with at least one programming language (such as Python, Java).
Good to have familiarity with basic data analysis, machine learning
Familiarity with databases and their basic principles, including tables, queries, and data manipulation.
Good to have familiarity with NumPy, Pandas for data manipulations
A working environment for running code and executing machine learning algorithms, such as Jupyter Notebook, Google Colab, or a local development setup.
Description
Who this course is for:
Data engineers, database administrators and data professionals curious about the emerging field of vector databases.,Data scientists and analysts interested in exploring advanced AI techniques.,Machine learning engineers seeking to enhance their knowledge of vector databases and their applications.,AI researchers and practitioners looking to leverage vector databases for generative AI models.,Software developers interested in integrating vector databases into their applications.,Students and academics studying AI, machine learning, or data science who want to expand their knowledge in this specialized area.,Individuals with a technical background or a strong interest in AI and databases, eager to explore cutting-edge technologies shaping the future of AI and ML.
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