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.
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
