Unlock the future of AI with PromptFlow in Azure Machine Learning & AI studio. From automation with GitHub Actions to scalability with Azure API Management, learn how PromptFlow is changing the game for LLMOps.
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Data Science & Data Engineering blogs
Thanks for reading. Here you will find a huge range of information in text, audio and video on topics such as Data Science, Data Engineering, Machine Learning Engineering, DataOps and much more. The show notes for “Data Science in Production” are also collated here.
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Discover why your business needs to focus on fine-tuning datasets now. With AI technology evolving, having the right data can set you apart.
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Azure's PromptFlow is a cutting-edge tool within the Azure ML suite designed to enhance the development and deployment of Large Language Model (LLM) applications. It offers an intuitive interface for prompt engineering, real-time testing, and evaluation, ensuring prompts are optimized for accuracy and relevance.
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Managing costs in Azure OpenAI is crucial, especially with its pay-as-you-go model based on tokens. This blog looks at tools which can help maintain a balance between innovation and cost-efficiency.
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This blog discusses an AI-driven system that uses large language models (LLMs) to empower employees by identifying skill gaps and creating personalized learning paths. The system acts as a personal career coach, providing tailored feedback and growth opportunities.
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The blog post explores the potential of large language models (LLMs), like OpenAI's GPT-4, in enhancing Business Event Analysis & Modeling (BEAM) sessions. The fusion of BEAM and LLMs can revolutionize the design of data warehousing and business intelligence by providing scalability, accessibility, consistency, automatic documentation, and rapid prototyping.
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Automating code documentation can save businesses significant time and money, while improving code quality, consistency, and developer productivity. With the ChatGPT API, developers can quickly and easily add in-line comments to code files, enhancing readability and maintainability. By automating this process, companies can save up to thousands of hours per year and ensure that documentation is consistent and accurate.
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