This repo contains a collection of demos, scripts, code samples, and notebooks that demonstrate how to use Google Cloud Platform services. The repo is organized by service, and each service directory contains a README file that provides more information about the demos, scripts, and code samples in that directory.
The demos in this repo are designed to be runnable, so you can easily try them out on your own. The scripts and code samples in this repo can be used as a starting point for your own projects, or you can modify them to fit your specific needs.
The notebooks in this repo are Jupyter notebooks, which are a great way to experiment with GCP services and to share your work with others.
I hope you find this repo helpful!
Google Cloud offers a wide range of AI and machine learning services, including:
- Pre-trained ML APIs: These APIs provide access to pre-trained machine learning models that can be used for a variety of tasks, such as image classification, natural language processing, and speech recognition.
- AutoML: These services help you build and deploy machine learning models without having to write any code.
- Image: AutoML Vision can be used to build image classification and object detection models.
- Language: AutoML Natural Language can be used to build text classification, entity extraction, and question answering models.
- BigQuery ML: This service makes it easy to build and deploy machine learning models on BigQuery data.
- Vertex AI & Custom ML: These services provide a fully managed platform for building and deploying custom machine learning models.
- AI Industry Solutions: These solutions provide pre-built AI models and tools for specific industries, such as healthcare, retail, and finance.
- Document AI: This solution helps you extract structured data from documents, such as invoices, contracts, and medical records.
- Healthcare Natural Language: This solution helps you analyze healthcare data, such as clinical notes and electronic health records.
- Discovery AI: This solution helps you find and analyze unstructured data, such as social media posts and customer reviews.
- End-to-End MLOps: These services help you automate the machine learning lifecycle, from data preparation to model deployment and monitoring.
- Generative AI: These services help you create new content, such as images, text, and music, using machine learning.
- Image: This service can be used to generate realistic images from text descriptions.
- Language: This service can be used to generate text, translate languages, and write different kinds of creative content.
Google cloud end-to-end demos with use cases
- Entity extraction using Document AI
- Real time anomaly detection using Timeseries Insights API