Author(s): Siavash Yasini

Originally published on Towards AI.

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Whether you are actively pursuing a career in data science and machine learning, or just a data hobbyist building creative apps for fun, portfolio projects can be your golden ticket to stand out in a competitive field and demonstrate your data superpowers in action. End-to-end portfolio projects are also a great way to go beyond the basics and apply your theoretical knowledge to solving real-world (or even unreal but just plain fun) problems. They can also help you expand your professional network, connect with like-minded folks who love building data projects, and — more importantly — get noticed by that recruiter or hiring manager who is on the hunt for brilliant talent just like you!

Tools like Streamlit make it extremely easy to bring your ideas to life and can be leveraged to build a wide array of cool things: fancy machine-learning-powered apps, interactive data stories, or even fun games and puzzles. Whether you’re building a portfolio to give your job application a boost, or you just love building simply as a creative outlet, all you need for an amazing portfolio project is a four-step plan:

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Published via Towards AI