Azure OpenAI Service, a service from Microsoft's Azure suite available in preview, includes pre-generated AI models that enable users to apply advanced coding and language models to a variety of use cases, enabling new reasoning and comprehension capabilities for building applications. Users can apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data.
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Streamlit
Score 8.9 out of 10
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Streamlit is an open-source Python library designed to make it easy to build custom web-apps for machine learning and data science, from the company of the same name in San Francisco. Streamlit also hosts its community's Streamlit Component offered via API to help users get started.
- Don't want to pay Tableau $1,000 / seat? Use Streamlit - Want fully custom views and navigation? Use Streamlit - Want access to Machine Learning and not just your dev team? Use Streamlit - Want to keep things internal and secure? Use Streamlit - Want your Data Science team to be able to crank out projects quickly? Use Streamlit - Sick of Jupyter Notebooks and Business Leaders not understanding them? Use Streamlit Our D.S. strategy has moved completely to delivering pages in Streamlit. I can hand an executive a Jupyter notebook and it'll get lost in translation. I can give them sign-in access to a page and they can answer all of their own "What-If?" questions! We've used Streamlit to productize our Data Science and Machine Learning capabilities.
Recent Security issues (they quickly released an update to combat this though...)
Requires a bit of HTML knowledge to really customize. If you're going quick, you don't need HTML though. Streamlit commands will pump your page out fast.
Azure OpenAI is easy to deploy, manage and scalable solution for Gen AI application, they have really good SDK to call their APIs securely. anyone with a background in backend engineering can easily use their APIs to make their ideas into reality
1. Open AI is best at giving accurate answers. 2. It is secure and more trustworthy 3. Most of our client using Azure cloud so it becomes go to choice for them. 4. Scalable as it handles 1000s of request per minute. 5. SDKs are easy to use and well documented.
I started using Streamlit when it first came out and thought it was really useful and powerful. A few years later and they've really hit their stride! The features / widgets / materials they provide have been well researched, well designed, and well implemented. I will take Streamlit to any future companies I go to as well as be a strong promoter wherever I'm currently at. It's free. It's easy to use. It is really powerful. Sure? You could go pay for a larger system but your Data Science team should be able to handle Streamlit easily. I'd argue a non-technical person spending a few weeks in python could pick up Streamlit really quickly.
