- Open the Azure link above in a new tab for a guided analysis of the Iris Dataset. This case study will introduce the following fundamental concepts of data science:
- Installing the data science libraries
- Loading the dataset.
- Summarizing the dataset.
- Visualizing the dataset.
- Evaluating some algorithms.
- Making some predictions.
- Clone the project to your own github (there's a button to clone within azure!)
- Get started on the case study! There are guided solutions if you prefer a side by side approach.
- https://github.com/jakevdp/PythonDataScienceHandbook/blob/97c8c91c5932f2b2a58bb97c000506f636ee661a/notebooks/05.02-Introducing-Scikit-Learn.ipynb
- https://analyticsindiamag.com/start-building-first-machine-learning-project-famous-dataset/
- https://machinelearningmastery.com/machine-learning-in-python-step-by-step/
- https://machinelearningmastery.com/k-fold-cross-validation/
- https://medium.com/codebagng/basic-analysis-of-the-iris-data-set-using-python-2995618a6342