Search Results for "cloud"

DevOps Exercises is a massive, community-maintained collection of questions, tasks, and mini-challenges that cover the breadth of modern DevOps and platform engineering. It spans Linux, networking, Docker, Kubernetes, CI/CD, monitoring, cloud providers, security, and even soft skills and troubleshooting. The idea is to give candidates and teams a realistic practice ground for interviews, certifications, and day-to-day operational work. Because it’s structured as Q&A and exercises, you can go through it progressively or dip into specific domains where you need strengthening. ...

The data-science-on-gcp repository is a comprehensive collection of code examples and end-to-end workflows that accompany the book Data Science on the Google Cloud Platform, designed to teach developers how to build scalable data science and machine learning systems using Google Cloud services. It provides structured, chapter-aligned implementations that guide users through the full lifecycle of a data science project, including data ingestion, storage, processing, analysis, model training, and deployment. ...

AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional allennlp subcommands. ...