Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
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Updated
May 31, 2024 - Jupyter Notebook
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
Sample code and notes for my GCP courses on LinkedIn Learning
An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
Ship RAG based LLM web apps in seconds.
This repository compiles code samples and notebooks demonstrating how to use Generative AI on Google Cloud Vertex AI.
Showcasing Google Cloud's generative AI for marketing scenarios via application frontend, backend, and detailed, step-by-step guidance for setting up and utilizing generative AI tools, including examples of their use in crafting marketing materials like blog posts and social media content, nl2sql analysis, and campaign personalization.
Fraudfinder: A comprehensive lab series on how to build a real-time fraud detection system on Google Cloud
Transformers 3rd Edition
Build MLOps Pipelines in Minutes
Looker extension designed to give business users access to BigQuery and Vertex AI's machine learning capabilities.
AI Makerspace: Blueprints for developing machine learning applications with state-of-the-art technologies.
Machine Learning Pipeline for Semantic Segmentation with TensorFlow Extended (TFX) and various GCP products
Optimise Shopping feeds with Generative AI
Use the universal VDF format for vector datasets to easily export and import data from all vector databases
A NodeJS RAG framework to easily work with LLMs and embeddings
A Ruby Gem for interacting with Gemini through Vertex AI, Generative Language API, or AI Studio, Google's generative AI services.
Basic UI to chat with Google Gemini AI
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