In this liveProject, you’ll get hands-on experience using Jupyter Notebook in a real-world data science project. You’ll train a simple KNN classifier and use Jupyter, IPython, and the easy-to-use Markdown markup language to document and share your work. Your challenges will include customizing your notebooks, incorporating your notebooks into a data science project, and sharing your projects with the community on GitHub.

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This liveProject is for intermediate Python programmers at the start of their data science careers. Some experience with virtual environments and integrated development environments, as well as a markup language, will be useful but not essential. To begin this liveProject you will need to be familiar with:
TOOLS

- Intermediate Python

- Basics of scikit-learn
TECHNIQUES

- Basics of classification

- Basics of evaluating classifiers
you will learn

In this liveProject, you’ll master handy tools for documenting and sharing Python data science projects.

- Document work with Markdown

- Collaborate on Jupyter Notebook projects

- Render math formulas with embedded LaTeX

- Customize your notebooks

- Use Jupyter Notebook extensions

- Share work on GitHub