TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
created at Nov. 11, 2015, 2:21 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.
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.
links to conference publications in graph-based deep learning
created at Dec. 1, 2017, 2:48 p.m.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
created at March 6, 2016, 11:30 p.m.
Implementing a Neural Network from Scratch
created at Sept. 2, 2015, 9:30 a.m.
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
created at March 31, 2017, 7:26 p.m.
Implementation of various topic models
created at Aug. 29, 2014, 4:01 a.m.