Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
created at May 16, 2014, 7:24 p.m.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
created at Nov. 5, 2016, 6:21 p.m.
A complete daily plan for studying to become a machine learning engineer.
created at Oct. 9, 2016, 9:20 p.m.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
created at Jan. 14, 2013, 3:46 p.m.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
created at Nov. 11, 2015, 2:21 p.m.