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💫 Toolkit to help you get started with Spec-Driven Development
A smarter cd command. Supports all major shells.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
A pre-commit hook to check your Python dependencies against safety-db
the blessed package to manage your versions by scm tags
A Tutorial for Setting Python Development Environment with VScode and Docker
Kickstart your LLMOps initiative with a flexible, robust, and productive Python package.
Prevent cloud misconfigurations and find vulnerabilities during build-time in infrastructure as code, container images and open source packages with Checkov by Bridgecrew.
Draw datasets from within Python notebooks.
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Simple, unified interface to multiple Generative AI providers
A curated list of Large Language Model resources, covering model training, serving, fine-tuning, and building LLM applications.
Positron, a next-generation data science IDE
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
The book every data scientist needs on their desk.
List of books, blogs, newsletters and people!
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
This repo provides a customizable stack for starting new ML projects on Databricks that follow production best-practices out of the box.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Learn how to design, develop, deploy and iterate on production-grade ML applications.