Utility Functions for Production R Code (MazamaCoreUtils)A suite of utility functions providing functionality commonly needed for production level projects such as logging, error handling, and cache management.
Key Takeaways from AI Conference SF, Day 2： AI and Security, Adversarial Examples, Innovation
Last month, experts from the AI world came together for the Artificial Intelligence Conference at San Francisco to discuss insights, opportunities, challenges, and trends related to the rapidly expanding field of AI. The conference included hands-on trainings, tutorials, startup showcase (which was won by Clobotics), keynotes, sessions, expo, and social events.
How to create useful features for Machine Learning
Recently, a member of Data School Insiders asked the following question in our private forum:
New Poll： How Important is Understanding Machine Learning Models?
Deep Learning methods build very good prediction and classification models, but they are very hard for humans to understand.
Additional Strategies for Confronting the Partition Function
In the previous post we introduced Boltzmann machines and the infeasibility of computing the gradient of its log-partition function (\nabla_{\theta}\log{Z}). To this end, we explored one strategy for its approximation: Gibbs sampling. Gibbs sampling is a viable alternative because the expression for this gradient simplifies to an expectation over the model distribution, which can be approximated with Monte Carlo samples.
Fringe FM conversation on AI Ethics
A few weeks ago, I had a lively conversation with Matt Ward for the Fringe FM podcast, where we discussed artificial intelligence, its applications, and the ethical implications thereof.
Machine Learning Basics – Random Forest
A few colleagues of mine and I from codecentric.ai are currently working on developing a free online course about machine learning and deep learning. As part of this course, I am developing a series of videos about machine learning basics – the first video in this series was about Random Forests.
Are petrol prices in Australia fair?
Petrol is a product that used by most of Australians. So people are pretty sensitive to price changes, especially when the fuel become more expensive. With prices reaching $1.6 for unleaded the debates are becoming more and more hot.
Using deep learning on AWS to lower property damage losses from natural disasters
Natural disasters like the 2017 Santa Rosa fires and Hurricane Harvey cost hundreds of billions of dollars in property damages every year, wreaking economic havoc in the lives of homeowners. Insurance companies do their best to evaluate affected homes, but it could take weeks before assessments are available and salvaging and protecting the homes can begin. EagleView, a property data analytics company, is tackling this challenge with deep learning on AWS.
Use Pseudo-Aggregators to Add Safety Checks to Your Data-Wrangling Workflow
One of the concepts we teach in both Practical Data Science with R and in our theory of data shaping is the importance of identifying the roles of columns in your data.