yadongli / Nyumath2048

Presentations for JuliaCon

Code to accompany my upcoming book "Deep learning with PyTorch Book " from Packt

Bayesian Machine Learning, https://us.pycon.org/2017/schedule/presentation/232/

Python Tutorials

Pytorch code for BMVC 2018 paper

🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease

INFO 490: Advanced Data Science, offered in the Spring 2016 Semester at the University of Illinois

A containerised platform for Geographic Data Science

🍧 A repository that contains courses I have taken on DataCamp

PyCon 2017 tutorial on time series analysis

Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.

Stock Market Analysis with RNN and Time Series

An end-to-end walkthrough of the winning submission by grt123 for the Kaggle Data Science Bowl 2017

A recommendation system using tensorflow

Code and notebooks for Econometric Theory

environment setup for strata conference 2018

intro to machine learning - reverse engineering phenomena