Edit sound with Python NumPy: Improve code performance 1000x
Increase code performance 1000x times in Python NumPy by managing well big arrays & vectors in a sound editing program
Programming is one of the most flexible fields I know of. You can create a program that achieves a certain task in so many ways. However, that does not mean that all ways are equal. Some are better than others. That is especially visible when your program has to work with big data. Working with big data means working with gigantic arrays and matrices.
You can create a program that achieves the same task like the other one, but it does so 1000 times faster. It all depends on how you code and which coding practices you use. And this is what you will learn here. You will learn the good and the bad coding practices, so that you would learn to code the right way when dealing with big data.
In this 100% project based course, we will use Python, the Numpy and the Moviepy library to create a fully functional sound processing program. This program will import your videos in sequence, extract their audio, automatically identify the silent intervals in that audio, and then cut them out while still keeping some silence on the edges to preserve a bit of pause in between sentences.
What you’ll learn
- Code optimization in Python using the NumPy library
- Sound processing in Python using the MoviePy library
- Fundamentals of digital images
- Applying code optimization to binarize digital images
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