Implementation of various topic models
updated at April 4, 2024, 12:27 p.m.
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
updated at April 28, 2024, 11:29 a.m.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
updated at May 8, 2024, 2:37 a.m.
Implementing a Neural Network from Scratch
updated at May 10, 2024, 2:57 p.m.
links to conference publications in graph-based deep learning
updated at May 11, 2024, 7:39 a.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.
updated at May 11, 2024, 5:19 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 ;)
updated at May 11, 2024, 9:19 p.m.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
updated at May 12, 2024, 4:07 a.m.