Remove Explainability Remove ML Engineer Remove Responsible AI
article thumbnail

Top Artificial Intelligence AI Courses from Google

Marktechpost

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.

article thumbnail

Explainable AI (XAI): The Complete Guide (2024)

Viso.ai

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning Blog

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

article thumbnail

The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

AWS Machine Learning Blog

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

article thumbnail

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

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. This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking.

article thumbnail

Bria 2.3, Bria 2.2 HD, and Bria 2.3 Fast are now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

These advanced models from Bria AI generate high-quality and contextually relevant visual content that is ready to use in marketing, design, and image generation use cases across industries from ecommerce, media and entertainment, and gaming to consumer-packaged goods and retail. model using SageMaker JumpStart. Overview of Bria 2.3,

article thumbnail

Announcing the First Sessions for ODSC East 2024

ODSC - Open Data Science

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.