Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It also introduces Google’s 7 AI principles.

Artificial Intelligence 108

Artificial Intelligence Artificial Intelligence BERT Computer Vision 108

AWS Machine Learning Blog

NOVEMBER 30, 2023

It also integrates with Machine Learning and Operation (MLOps) workflows in Amazon SageMaker to automate and scale the ML lifecycle. FMEval provides the ability to perform evaluations for both LLM model endpoints or the endpoint for a generative AI service as a whole. What is FMEval? Tomer Shenhar is a Product Manager at AWS.

Large Language Models 83

Large Language Models LLM Algorithm Responsible AI 83

ODSC - Open Data Science

JANUARY 10, 2024

Andre Franca | CTO | connectedFlow Explore the world of Causal AI for data science practitioners, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. Takeaways include: The dangers of using post-hoc explainability methods as tools for decision-making, and where traditional ML falls short.

Large Language Models 52

Large Language Models LLM Deep Learning ML 52

AWS Machine Learning Blog

MARCH 14, 2024

Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval.

Generative AI 94

Generative AI LLM AI AI 94

The MLOps Blog

JUNE 27, 2023

Model governance and compliance : They should address model governance and compliance requirements, so you can implement ethical considerations, privacy safeguards, and regulatory compliance into your ML solutions. Integration with ML tools and libraries: Provide you with flexibility and extensibility.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69