Python Programming Lecture Series Part-16 (Ordinary Least Squares Algorithm)

In this comprehensive session, we'll walk you through the concepts, applications, and practical implementations of the OLS Optimization Algorithm. Get ready for an exciting journey where we'll use various methods to compute model parameters, including a manual approach, leveraging the power of NumPy functions, and harnessing the convenience of the sklearn fit function.
Whether you're a seasoned data scientist or just getting started in the field of Machine Learning, this video has something for everyone. We'll demonstrate each step using the user-friendly Jupyter Lab Python interface, making it easy for you to follow along and gain a deep understanding of Optimization Algorithms in action.
By the end of this video, you'll have a solid grasp of how Optimization Algorithms like OLS work and their significance in building robust Machine Learning models.
Lecture notes on OLS:
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