#Google Cloud

Access a plethora of learning resources around Generative AI on Google Cloud's Vertex AI, including notebooks and code samples for developing and managing generative AI workflows. This extensive repository highlights the use of Vertex AI for creating solutions in image, speech processing, and conversational models.

Realm provides a robust adversary emulation framework that excels in scalability, reliability, and automation, making it suitable for large-scale operations. Features such as Eldritch, a Pythonic DSL, facilitate security tasks, while seamless multi-host management and native GCP integration boost attack efficiency. A stateless server architecture supports flexible deployments. With easy-to-use design and thorough documentation, Realm promotes an effective experience and engages a community-driven development approach.

Discover Jupyter notebooks tailored for Vertex AI that transition software engineers from basic to advanced machine learning levels. The repository provides various model architectures including DNN, CNN, and RNN, as well as resources for efficiently deploying models using TensorFlow, PyTorch, and Scikit-learn on Google Cloud. Users can enhance their skills via structured labs, solutions, and comprehensive setup instructions. Emphasizing hands-on experience with TensorFlow, it is well-suited for beginners. Contributions are currently limited to Google employees, fostering internal growth.

Explore KITT, an AI-driven WebRTC conference tool that enhances communication using ChatGPT. KITT enhances video call communication through ChatGPT-powered AI. It leverages GCP for speech-to-text and text-to-speech, ensuring seamless interactions. Deployed on LiveKit with OpenAI support, KITT exemplifies the integration of NextJS and cloud services. Try the online demo to see AI's impact on virtual meetings.

TensorFlow Cloud facilitates the migration from local to cloud platforms for Keras and TensorFlow models, streamlining distributed training on Google Cloud. Features, including the 'run' API, allow for smooth scaling using Python scripts or notebooks. It offers configurations like OneDeviceStrategy, MirroredStrategy, and TPUStrategy to maximize cloud utilizations, suitable for varied machine learning workflows. Basic requirements include Python, Docker, and Google Cloud, ensuring user-friendly deployment with flexible distribution strategies.

This repository offers diverse resources like code samples and notebooks for developing and managing AI workflows with Google Cloud's Vertex AI. It supports both beginners and experts in utilizing its AI platform, providing guides on model development, deployment, and explanation. The community can contribute to enhance these resources, making it an evolving hub for machine learning exploration.

Discover a curated list of HashiCorp's Terraform resources, helping users effectively manage production infrastructure. This platform offers official resources, community modules, guides, and supports cloud services like AWS, Azure, and Google Cloud, catering to both beginners and experts in dynamic environments.

This script allows websites with JobPosting or BroadcastEvent structured data to be indexed on Google in less than 48 hours using the Google Indexing API. It necessitates Node.js, Google Search Console, and Google Cloud accounts, ensuring clear site visibility while not influencing search rankings. Utilize simple installation options—via CLI, repository clone, or npm module—facilitating quick deployment. API service enabling is mandatory, and large site indexation might require patience due to quota retry mechanisms.

Terraformer is a CLI tool that reverse engineers existing infrastructures into Terraform and JSON files. It supports providers like AWS, Google Cloud, and Azure, allowing users to manage and upgrade infrastructure effectively using provider updates. Key features include resource importing, service and ID filtering, and customizable file structures.

Discover a curated collection of Kubernetes resources, guides, and tutorials tailored for developers and IT professionals. Gain insights into Kubernetes deployment, scaling, and management across different environments, while exploring its key concepts, historical context, and community contributions. Stay informed with the latest releases and expand your expertise through diverse educational content and systematic guides.