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Jupyter notebook with a study on Kalman Filtering on simulated data
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Kalman filtering with constant velocity.ipynb
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README.md

README.md

KalmanFiltering_ConstantVelocity

Python implementation of a case study in Module 5 of the MITProfessionalX course "Data Science: Data to insights".

The case study is: "Module 2 Case Study - Kalman Filtering – Tracking Location of Object Moving with Constant Velocity". This case study is about tracking the state of an object moving with constant velocity, using Kalman Filtering, when we have noisy measurements of its velocity in 2 dimension.

References


The notebook

Kalman filtering with constant velocity.ipynb


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