Predictive Modelling with Azure Machine Learning Studio
9819 ya inscrito
9819 ya inscrito
In this project, we will use Azure Machine Learning Studio to build a predictive model without writing a single line of code! Specifically, we will predict flight delays using weather data provided by the US Bureau of Transportation Statistics and the National Oceanic and Atmospheric Association (NOAA). You will be provided with instructions on how to set up your Azure Machine Learning account with $200 worth of free credit to get started with running your experiments! This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Artificial Intelligence (AI)
En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:
Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.
En un video de pantalla dividida, tu instructor te guía paso a paso
por DA10 de sep. de 2020
What a nice way to learn, understand and practice along with the instructor. I like this format.
por AG16 de jun. de 2020
The educational activities are designed to ensure that there must be a successful take away for participants. I have greater confidence with incorporating educational technologies in my teaching.
por UG15 de oct. de 2020
model training model is not full explain it as explain in course
por TT25 de sep. de 2020
We got great opportunity to practice Azure Machine Learning environment. Thank you.