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Machine Learning for Signal Processing


In this tutorial, we will understand how to use machine learning tools for signal processing. In particular: data compression and noise removal. To do so, we will discuss Principal Component Analysis (PCA) and explore how linear algebra can be used for these and other applications.

What you’ll learn

  • How does PCA work
  • When PCA doesn’t work
  • Few other machine learning techniques
Sara Malvar
Sara Malvar

Sr. Research Software Development Engineer at Microsoft

Sara holds a bachelor’s degree in electrical engineer and a PhD in engineering from the University of São Paulo (Brazil). She worked at IBM and is currently working with Deep Learning solutions for Shell and IBM in the Research Centre for Gas Innovation and the Center for Artificial Intelligence. She has been working as a mentor and instructor of Data Science and Machine Learning courses for over 4 years.

We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!