Knowledge graphs are network graphs that link related concepts and properties together to create a form of inferencing engine, with knowledge engineering being the programming aspect of graph usage. Explore how knowledge graphs are created and queried, how they are used as part of a broader form of enterprise metadata management, and how they tie into ML and the IoT.
This article was written by Pranjal Srivastava. Sequence prediction problems have been around for a long time. They are considered as one of the hardest… Read More »Essentials of Deep Learning : Introduction to Long Short Term Memory
Heating, ventilation, and air conditioning of buildings accounts alone for nearly 40% of the global energy demand [1]. The need for Energy Savings has become increasily foundamental to fight Climate Change. We… Read More »Reinforcement Learning to Reduce Building Energy Consumption
Summary: Autonomous vehicles (AUVs) and many other systems that need to accurately perceive the world around them will be much better off when image classification… Read More »We See in 3D – So Should Our CNN Models
According to Wikipedia, an ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a… Read More »Artificial Neural Networks in a Nutshell
INTRODUCTION TO THE RESEARCH QUESTION The research was conducted to find out what price maximises profit without sacrificing the high demand for the product due… Read More »Price Optimisation Using Decision Tree (Regression Tree) – Machine Learning
