ThomasDing2016
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Data Processing Advanced: a course on scientific computing with Numpy/Scipy
The source code for 'Data Structures and Algorithms in Python' by Goodrich, Tamassia, Goldwasser
Materials for the GIAN Course "Modern Applications of Numerical Linear Algebra Methods"
Repository for materials/codes from Kording lab teaching 2016
Reproducing MNIST results in Ciresan 2012: http://arxiv.org/abs/1202.2745
Code samples for my book "Neural Networks and Deep Learning"
Vectorized implementation of a general feedforward neural network in Python
Deep learning tutorial for PyData
BUS 41204: Machine Learning
Lectures on scientific computing with python, as IPython notebooks.
Materials for EECS 445, an undergraduate Machine Learning course taught at the University of Michigan, Ann Arbor.
this is a python module for creating, training and applying hidden Markov models to discrete of continuous observations. Includes forward/backward viterbi
Machine learning library written in readable python code
iPython notebooks on tutorial topics for PMR course
Solutions for Machine Learning Specialization MOOC offered by University of Washington.
Python Data Science Handbook: full text in Jupyter Notebooks
Data driven lane change detection using US101 highway data, HMMs, and change point detetion.
TensorFlow: Viterbi, Forward-Backward and Baum Welch with a Hidden Markov Model (HMM)
Advanced Statistical Computing at Vanderbilt University Medical Center's Department of Biostatistics
Code for Jurafsky and Martin Textbook
This repository contains materials for demos, tutorials, and talks by Dato Inc.
Running EM algorithm to group protein sequences
Notebook of implementation of EM algorithm for Gaussian mixtures
Interactive tutorial on the Forward-Backward Expectation Maximization algorithm
Implementation of Bagging and Adaboost, and analysis of their effects on the bias-variance tradeoff.
📧 Implement Naive Bayes and Adaboost from scratch and use them to filter spam emails.