noahgift/pragmaticai
📚 Tutorialnoahgift
A practical guide to building and deploying cloud-based machine learning solutions across AWS, Azure, and GCP.
Pragmatic AI provides a hands-on approach to cloud-based machine learning, moving beyond academic concepts to focus on production-ready systems. The project covers the full lifecycle of AI development, including data preparation, model training, and deployment using serverless architectures like AWS Chalice and Step Functions. It emphasizes the use of Python, IPython, and visualization libraries like Plotly and Seaborn to analyze and interpret data. By focusing on multi-cloud strategies, it teaches users how to navigate the specific tools and APIs provided by AWS, Azure, and GCP. The repository acts as a companion to the book, offering a structured environment for learning how to operationalize ML models in the cloud, manage infrastructure as code, and build scalable AI services that integrate seamlessly with existing cloud ecosystems.
💡Highlights
- ├─Multi-cloud AI deployment patterns
- ├─Serverless ML with AWS and GCP
- └─Production-ready Python workflows
🎯For
- ├─Machine Learning Engineers
- ├─Cloud Architects
- └─Data Scientists