
Introduction to Data Governance for Machine Learning Systems: Fundamental Principles, Critical Practices, and Future Trends
Introduction to Data Governance for Machine Learning Systems: Fundamental Principles, Critical Practices, and Future Tre...
Introduction to Data Governance for Machine Learning Systems: Fundamental Principles, Critical Practices, and Future Tre...
Building Applications with Large Language Models: Techniques, Implementation, and Applications Author:by Bhawna Singh (A...
Unlocking Data with Generative AI and RAG: Enhance generative AI systems by integrating internal data with large languag...
Unlocking the Power of Auto-GPT and Its Plugins: Implement, customize, and optimize Auto-GPT for building robust AI appl...
Hands-On Blockchain for Python Developers – Second Edition 版本: Empowering Python developers in the world of block...
15 Math Concepts Every Data Scientist Should Know: Understand and learn how to apply the math behind data science algori...
Reliability and Risk Analysis (What Every Engineer Should Know) Author:by Mohammad Modarres (Author), Katrina Groth (Aut...
Advanced Fractal Graph Theory and Applications Author:by P. Tharaniya (Author), G. Jayalalitha (Author), Pethuru Raj (Au...
Mathematics For Engineers – Volume 2: Integral Calculus, Taylor And Fourier Series, Calculus For Multivariable Functions...
RAG-Driven Generative AI: Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone...