Machine learning in Python with scikit-learn - Getting started in scikit-learn with the famous iris dataset

Now that we've set up Python for machine learning, let's get started by loading an example dataset into scikit-learn! We'll explore the famous "iris" dataset, learn some important machine learning terminology, and discuss the four key requirements for working with data in scikit-learn. Download the notebook: https://github.com/justmarkham/scikit-learn-videos Iris dataset: http://archive.ics.uci.edu/ml/datasets/Iris scikit-learn dataset loading utilities: http://scikit-learn.org/stable/datasets/ Fast Numerical Computing with NumPy (slides): https://speakerdeck.com/jakevdp/losing-your-loops-fast-numerical-computing-with-numpy-pycon-2015 Fast Numerical Computing with NumPy (video): https://www.youtube.com/watch?v=EEUXKG97YRw Introduction to NumPy (PDF): http://www.engr.ucsb.edu/~shell/che210d/numpy.pdf WANT TO GET BETTER AT MACHINE LEARNING? HERE ARE YOUR NEXT STEPS: 1) WATCH my scikit-learn video series: https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A 2) SUBSCRIBE for more videos: https://www.youtube.com/dataschool?sub_confirmation=1 3) JOIN "Data School Insiders" to access bonus content: https://www.patreon.com/dataschool 4) ENROLL in my Machine Learning course: https://www.dataschool.io/learn/ 5) LET'S CONNECT! - Newsletter: https://www.dataschool.io/subscribe/ - Twitter: https://twitter.com/justmarkham - Facebook: https://www.facebook.com/DataScienceSchool/ - LinkedIn: https://www.linkedin.com/in/justmarkham/