Workshop 09/28/2022

This workshop is targeted towards those who are new to coding. This presentation will teach an individual how to analyze their personal Spotify data, create visualizations and prepare their data to be used in business processes. This demonstration will use Python so a new coder will understand foundational coding syntax that can be used in other languages.
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You’ve heard it before – Python vs MATLAB vs R vs … but in reality, programming languages are often used together! In this hands-on workshop, you’ll learn how to use MATLAB and Python together with practical examples. Specifically, you’ll learn how to:

– Call Python libraries from MATLAB
– Call user-defined Python commands, scripts, and modules
– Manage and convert data between languages
– Package MATLAB algorithms to be called from Python
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In this workshop, I would like to share my personal journey transitioning from an electrical engineer focusing on ultra-low power integrated circuit design to an AI Solution Architect. Through specific examples of how the two fields connect, I will discuss the fundamentals of deep learning and data-driven hardware design. I will start with my experience in semiconductor industry designing application-specific and data-dependent hardware for IoT systems and then discuss how this experience led to my career in AI specializing in areas including high performance computing, edge computing, and more recently, federated learning.

I hope the attendees will not only find the technical content informative but also see how growth mindset truly helped me find my career passion. Having a broad knowledge of the eco-system that supports AI applications – such as the hardware stack, hardware level optimization, and application-specific hardware design – can be very helpful to understanding and choosing the right platform for operational AI. I also hope to use this opportunity to connect with fellow AI/hardware enthusiasts in WiDS.
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The least squares method is one of the most widely used techniques in data science and is used to fit a linear model to data. In this workshop, we will study least squares problems from a linear algebraic perspective and discuss the techniques to solve them.

This workshop assumes that you have a basic understanding of linear algebra including concepts such as matrices, rank, range space, orthogonality, and matrix decompositions (Cholesky, QR, SVD).