intermediate Python • intermediate Python standard library • basics of scikit-learn • basics of classification • basics of evaluating classifiers
skills learned
collaborate on Jupyter Notebook projects • customize your notebooks • work with Jupyter Notebook extensions
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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prerequisites
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
features
Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from fellow participants.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
related titles
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Check your email for instructions on downloading Getting Started with Jupyter Notebook.