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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Future Blog Post
Published:
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Bayesian Analysis of Road Safety in the City of Toronto
Investigation of Road Safety in the City of Toronto using our own RShiny web-app and Bayesian semi-parametric logistic regression 
Exploration of Deep Generative Adversarial Networks in the Context of Image Style Transfer
Generative Adversarial Networks (GANs) have shown great ability to generate realistic images and transfer (artistic) styles between photographs and works of art
ML Malware Prediction in the Cloud
Large-scale implementation of ML production-level pipeline in PySpark across multiple Cloud providers
Bayesian Methods for Data Correlated in Time and Space
Exploration of semi-parametric modeling of CO$_2$ emissions over time in Hawaii and geospatial Malaria incidence in Gambia using the Integrated Nested Laplacian Approximation (INLA) approximate Bayesian framework 
Exploration of a Variety of Monte Carlo Methods in the Context of Logistic Classification when N < P
We study the benefits and mixing properties of different Monte Carlo algorithms when implementing a logistic classifier on the MNIST hand-written dataset. 
Analysis of Smoking Habits in the American Youth
I study the uptake of cigarette smoking (Bayesian Survival Analysis), as well as consumption of other tobacco products (Logistic Regression), in the 2015 American National Youth Tobacco Survey, a survey of American teenagers, aged 9 to 19 years old, which collected not only indicators on the usage of different tobacco products, but also demographic data. 
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
A Taste of Bayesian Hierarchical Models
Published:
This talk gives a very brief, conceptual introduction to the Bayesian framework for hierarchical Bayesian models, with a case study of road safety in the City of Toronto.
Tutorial on Approximate Bayesian Inference using INLA
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This is a direct application of the Integrated Nested Laplacian Approximation (INLA) framework for approximate Bayesian inference. In this tutorial we examined math achievement scores (MathAchieve in the MEMSS library) across schools and individuals as a hierarchical regression problem.
Elementary Tutorial on Artificial Neural Networks
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This hands-on tutorial served as an introduction to the principal concepts around building, training, and understanding Artificial Neural Networks (NNs).
Introduction to Data Science and ML Reasoning
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This talk served as an introduction to the building blocks and modern capabilities of Data Science and Machine Learning.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.