2019

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

Neural networks have made significant leaps in the image and natural language processing (NLP) recently. They’ve not only learned to recognize, localize and segment images;… Read More »Neural Machine Translation With Attention Mechanism: Step-by-step Guide

The amount of data generated today is astonishing. Research published by Seagate reports that by 2025, around 175 Zettabytes of data will be generated on… Read More »Data Science Applications In Various Industries

In fact, the business plans of the next 10,000 startups are easy to forecast: Take X and add AI. Find something that can be made… Read More »Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference?

Background Containerize your Apps with Docker and Kubernetes is an excellent free book from Gabriel N. Schenker You can download the whole book by registering… Read More »Free book – Containerize your Apps with Docker and Kubernetes and impact of containers for AI on Edge devices

The following picture shows the differences between the Z Test and T Test. Not sure which one to use? Find out more here: T-Score vs. Z-Score.