As discussed, trying to do projects in data science that come from open sources, and then putting them with your resume and portfolio good for improving your competitiveness as an applicant to roles in data science. One exciting subject is real-time audio analysis. An open-source project on it would add a lot of value to a portfolio and resume.
Here is the link to the project:
This project is one that I really enjoy. It was made by Xander Steenbrugge, speaker for the past 2 DataHack Summits. The Python library helps us to do real-time analysis of audio.
As Xander says on his GitHub site:
“A simple package to do realtime audio analysis in native Python, using PyAudio and Numpy to extract and visualize FFT features from a live audio stream.”
FFT refers to Fast-Fourier Transform. It’s an awesome tool to add to your skillset as it enables you do deal with a vast array of issues. If you’re not familiar with FFT, then I encourage you to learn more here.
Also, if you haven’t dealt with data in audio form previously, then here’s a link below to an article to learn about it: