Algorithm ML Engineer Responsible AI 
Unite.AI
FEBRUARY 22, 2024
In the rapidly evolving realm of modern technology, the concept of ‘ Responsible AI ’ has surfaced to address and mitigate the issues arising from AI hallucinations , misuse and malicious human intent. Bias and Fairness : Ensuring Ethicality in AI Responsible AI demands fairness and impartiality.
AWS Machine Learning Blog
JANUARY 28, 2025
By investing in robust evaluation practices, companies can maximize the benefits of LLMs while maintaining responsible AI implementation and minimizing potential drawbacks. To support robust generative AI application development, its essential to keep track of models, prompt templates, and datasets used throughout the process.
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AWS Machine Learning Blog
DECEMBER 9, 2024
MLflow , a popular open-source tool, helps data scientists organize, track, and analyze ML and generative AI experiments, making it easier to reproduce and compare results. The scenario is using the XGBoost algorithm to train a binary classification model. Outside of work, he enjoys playing football and reading.
Towards AI
JANUARY 6, 2025
AI engineering professional certificate by IBM AI engineering professional certificate from IBM targets fundamentals of machine learning, deep learning, programming, computer vision, NLP, etc. Build expertise in computer vision, clustering algorithms, deep learning essentials, multi-agent reinforcement, DQN, and more.
AWS Machine Learning Blog
NOVEMBER 30, 2023
Verifiable evaluation scores are provided across text generation, summarization, classification and question answering tasks, including customer-defined prompt scenarios and algorithms. It also integrates with Machine Learning and Operation (MLOps) workflows in Amazon SageMaker to automate and scale the ML lifecycle. What is FMEval?
AWS Machine Learning Blog
MAY 9, 2024
Governance Establish governance that enables the organization to scale value delivery from AI/ML initiatives while managing risk, compliance, and security. Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI.
AWS Machine Learning Blog
NOVEMBER 14, 2024
Use case and model governance plays a crucial role in implementing responsible AI and helps with the reliability, fairness, compliance, and risk management of ML models across use cases in the organization. It helps prevent biases, manage risks, protect against misuse, and maintain transparency.
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