Keras [Chollet, François. “Keras (2015).” (2017)] is a popular deep learning library with over 250,000 developers at the time of writing, and over 600 active… Read More »Tech Talk with Rowel Atienza: Is Keras the Perfect Deep Learning Library in Python?
The use of training, validation and test datasets is common but not easily understood. In this post, I attempt to clarify this concept. The post… Read More »Three-way data splits (training, test and validation) for model selection and performance estimation
By Pranay Agarwal and Betsy Romeri. “They just don’t understand me. I provide them with all the necessary details, all the data and analysis possible, but… Read More »How to Set the Stage for a Successful Data Science Project: A Sales Person’s Perspective
The problem with Cambridge Analytica is not the privacy breach TL;DR: Echo chambers created by CA or other political marketing firms are bad for democracy,… Read More »The problem with Cambridge Analytica is not (just) the privacy breach
We are living in a time of slow yet steady insurgence of data science and AI in our lives. It spans more industries than we’d… Read More »Remarkable Applications of Data Science
Landing a man on the moon 50 years ago was a true feat of genius, and an outstanding collaboration between many different stakeholders with many… Read More »Data Science Lessons from the Apollo Moon Landing
Who is Data Scientist? “Data Scientists are like bikinis. What they reveal is suggestive, but what they conceal is vital.” – Aaron Levenstein, business professor at… Read More »Hiring Strategy – from Campus to Competition!
Bayesian Machine Learning (part – 4) Introduction In the previous post we have learnt about the importance of Latent Variables in Bayesian modelling. Now starting… Read More »Bayesian Machine Learning
Today, businesses need to be able to predict demand and trends to stay in line with any sudden market changes and economy swings. This is… Read More »How to Combine Different Methods for A 24-times Faster Time Series Prediction
Mobile health (mHealth) is considered one of the most transformative drivers for health informatics delivery of ubiquitous medical applications. Machine learning has proven to be… Read More »Machine Learning on Mobile: An On-device Inference App for Skin Cancer Detection
