Jupyter Notebook Workflow - DevOps for Data Science
DevOps is popular technology best practice and it is often used in combination with Python. The center of the universe for DevOps is the build server. The build server enables automation. This automation includes linting, testing, reporting, building and deploying code. This process is called continuous delivery.Copilot Explains - Error troubleshooting in Jupyter Notebooks
Data scientists and AI engineers love to work with Jupyter Notebooks because they make so much easier to look at the result of each and every data exploration step or data modeling experiment and take decisions accordingly. However, Jupyter notebooks are not immune to errors and sometimes understanding error messages - in particular if you aren’t a native English speaker or you are a beginner - and troubleshooting code might be painful and time consuming.Jupyter Experiences on Microsoft Azure
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much moreGuide to the Microsoft Azure Notebooks for Students
First published on MSDN on Jun 10, 2017 This is a guest post by Francine Tan, Microsoft Student Partner at Imperial College LondonHi I'm Francine, a Penultimate year Electrical and Electronic Engineering student and Microsoft Student Partner at Imperial College London check out my linkedin profile at https://www.
