Python examples on Google Cloud Platform (GCP). How to manage Compute Engine VM instances, Cloud Storage buckets, etc.
📣 Discord Bot to make announcements about upcoming sessions for the Fellows using Google Calendar and Calendly
Repository template to get started with Prefect Cloud & Google Cloud
Analysis of 311 Service Requests for the City of NYC (from 2010 to 2023) Tech: Prefect cloud, dbt core, BigQuery, Compute Engine, CloudRun, Artifact Registry, Terraform, Docker
HyperStream
Run Jupyter Notebooks (and store data) on Google Cloud Platform.
Automate health reporting and bring order in your Looker instance
Easy to study Data Platform for fun and profit
An end-to-end data engineering pipeline project that processes and analyzes Maintenance Work Orders using Mage, Docker, Google BigQuery, MariaDB, and Looker Studio. It features a seamless integration of cloud and open-source tools for scalable data storage, transformation, and visualization.
GCP 免费实例管理工具：创建免费实例、刷 AMD CPU、配置防火墙、远程执行脚本与本地预检
Ansible script to install DC/OS on Google Compute Engine
Intel Nexus – An enterprise-grade document intelligence platform that ingests PDFs, extracts structured knowledge (text, tables, images), and enables semantic search & RAG-based querying using FastAPI, Streamlit, and modern AI pipelines.
Interactive F1 Data Visualization app. Built using Python, Streamlit, and Pandas. Deployed via Streamlit Cloud to provide live racing insights 👇.
Automatically update Cloud DNS with GCE instance IP addresses upon startup or shutdown.
The Cloud SDK is a set of tools for Cloud Platform. It contains gcloud, gsutil, and bq, which you can use to access Google Compute Engine, Google Cloud Storage, Google BigQuery, and other products and services from the command-line. You can run these tools interactively or in your automated scripts.
NYC-311 Service Insights: A data-driven analysis of NYC's non-emergency service requests from 2010 to 2023
HyperStream
ML service for "Chatbot for optimizing customer operations" case given by Traveloka SG
Extract stock market data, then uploading it to GCP using Airflow, GCS, BigQuery and Spark
Speed benchmarking a 7B LLM on different gcloud VMs (using llama.cpp)
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