Last month, I gave a presentation titled Introduction to Probabilistic Machine Learning using PyMC3 at two local meetup groups (Bayesian Data Science D.C. and Data Science & Cybersecurity) in McLean, Virginia. The following is a summary of the concepts we discussed regarding Principled AI.
This study proposed a Bayesian nonparametric framework to capture implicitly hidden structure in time-series having limited data. The proposed framework, a Gaussian process with a spectral mixture kernel, was applied to time-series process for insider-threat detection. The proposed framework addresses two current challenges when analyzing quite noisy time-series having limited data whereby the time series are visualized for noticeable structure such as periodicity, growing or decreasing trends and hard coding them into pre-specified functional forms.
In case you missed them, here are some articles from November 2017 of particular interest to users of Probabilistic Programming Languages(PPL).
Incase you missed it, here is a recording of my talk on Introduction to Probabilisitic Machine Learning at the Las Vegas R & Data Science Meetup groups. I introduced probabilistic machine learning and probabilistic programming with Stan. I discussed the basics of machine learning from a probabilistic/Bayesian perspective and contrasted it with traditional/algorithmic machine learning
In case you missed my free webinar on “Model-Based Machine Learning”, here is the recording. If you have any questions, please do not hesitate to contact me.
It is now easier for R users to filter and search for ggplot2-extensions on the Gallery page. You can now search packages based on a filter like: if it is on CRAN; or if it is for a particular task e.g. time series, networks, tech, etc. It is also easier for R developers to add their extensions to this Gallery.
I am glad to announce that I shall be presenting a live webinar with Domino Data Labs on July 20, 2016 from 11:00 - 11:30 AM PST on Model-Based Machine Learning and Probabilistic Programming using RStan. If you are interested in adopting machine learning but are overwhelmed by the vast amount of learning algorithms, this webinar will show how to overcome that challenge.
In case you missed my talk at the 2016 Data Science Africa Workshop organized by the United Nations Global Pulse Lab, here is the recording. My talk was titled “Sustainable Urban Transport Planning using Big Data from Mobile Phones”.
I am excited to be invited by the United Nations Global Pulse lab to speak at the 2nd Data Science Africa Workshop scheduled to take place in Kampala, Uganda from 30th June to 1st July. I will be speaking particularly on “Data Science for Sustainable Cities”. My talk is titled: “Sustainable Urban Transport Planning using Big Data from Mobile Phones”.
In case you missed my free webinar on “Getting Started with Spatial Data Analysis with R”, here is the recording. If you have any questions, please do not hesitate to contact me.