Learn how to develop, deploy and iterate on production-grade ML applications.
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The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
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🛠 All-in-one web-based IDE specialized for machine learning and data science.
A comprehensive guide to building RAG-based LLM applications for production.
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
Enterprise-grade platform to generate and execute Cypress, Playwright, WebdriverIO, and Appium end-to-end tests from natural language requirements. (Appium is experimental and requires external mobile infrastructure.)
