Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
-
Updated
Jul 17, 2024 - Jupyter Notebook
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
Notebooks & Example Apps for Search & AI Applications with Elasticsearch
A collection of hand on notebook for LLMs practitioner
These are the Microsoft Semantic Kernel Workshop notebooks. It addresses AI agents, agents collaboration and, of course, kernel, plugins, planners and function calling
Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 , Agents.
This Git repository contains the source code and related files for a project focused on leveraging generative AI techniques for interactive data visualization. The repository includes the notebook, example dataset, and the configuration file necessary to implement a simple interactive data visualization tool using OpenAI API.
This is the Metric Coders repository containing all the notebooks for machine learning.
A collection of Jupyter notebooks, Streamlit apps, and Flask applications demonstrating various use cases and implementations of AutoGen Agents. This repository serves as a practical resource for readers to explore and implement use cases discussed in my blogposts.
Notebooks that use LLMs to work with historical documents and artefacts
This repository contains a collection of machine learning examples implemented in Jupyter Notebooks. Each notebook demonstrates a different machine learning technique or algorithm, along with explanations and code examples.
This repository is a hub for data science enthusiasts, offering a diverse collection of projects, notebooks, and resources covering topics such as data analysis, machine learning, deep learning, and generative AI. Explore innovative ideas, contribute to cutting-edge research, and enhance your skills in the dynamic field of data science
Add a description, image, and links to the genai topic page so that developers can more easily learn about it.
To associate your repository with the genai topic, visit your repo's landing page and select "manage topics."