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Explainable Artificial Intelligence (XAI) for AI & ML Engineers

Analytics Vidhya

Introduction Hello AI&ML Engineers, as you all know, Artificial Intelligence (AI) and Machine Learning Engineering are the fastest growing filed, and almost all industries are adopting them to enhance and expedite their business decisions and needs; for the same, they are working on various aspects […].

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ML Engineering is Not What You Think — ML Jobs Explained

Towards AI

How much machine learning really is in ML Engineering? But what actually are the differences between a Data Engineer, Data Scientist, ML Engineer, Research Engineer, Research Scientist, or an Applied Scientist?! Data engineering is the foundation of all ML pipelines. It’s so confusing!

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Direct Preference Optimization, Intuitively Explained

Towards AI

ML Engineers(LLM), Tech Enthusiasts, VCs, etc. Anybody previously acquainted with ML terms should be able to follow along. How advanced is this post? Replicate my code here: [link] or through Colab PPO stands for proximal policy optimization in the context of solving RF problems.

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Explain text classification model predictions using Amazon SageMaker Clarify

AWS Machine Learning Blog

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). In this post, we illustrate the use of Clarify for explaining NLP models.

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12 Can’t-Miss Hands-on Training & Workshops Coming to ODSC East 2025

ODSC - Open Data Science

Explainable AI for Decision-Making Applications Patrick Hall, Assistant Professor at GWSB and Principal Scientist at HallResearch.ai Explainability is essential for building trustworthy AI, especially in high-stakes applications. By the end, youll have the knowledge and practical experience to implement AI agents in your own projects.

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Accelerate your ML lifecycle using the new and improved Amazon SageMaker Python SDK – Part 1: ModelTrainer

AWS Machine Learning Blog

The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK ( SageMaker Core ) provides access to full breadth of SageMaker features and configurations, allowing for greater flexibility and control for ML engineers. 8B model using the new ModelTrainer class.

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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 includes guidance on using Google Tools to develop your own Generative AI applications.