Did you know that the “e” in e-learning means electronic? As such, e-learning is defined as any form of learning delivered to an electronic device such as a computer, via a channel like the Internet. The next development was mLearning. As for the “m” of m-learning, this stands for mobile. As such, m-learning encompasses all
M-learning has many advantages that we do not realize. Smartphones, nowadays, everyone has one or at least wants one. People use their smartphones for entertainment, to connect with family and friends, to stay updated, for online shopping and many more. The number of smartphone users keeps increasing every day since the past few years, and
Mobile learning, also called M-learning or mLearning, is any type of content that is developed or consumed on mobile devices and apps used in the classroom, such as smartphones and tablets, and including anything from podcasts to full eLearning courses. It’s possible to learn whenever and wherever you want, as long as you have a
In previous topics we had discuss the term of Self-supervised learning. In general Self-supervised learning is for training computers to do tasks without humans providing labeled data. Is Self-supervised learning is better than supervised learning? Supervised learning requires labelled data. That data is typically labelled by a domain expert, i.e. someone who is expert at
Let’s pick a country to be specific, for easy in specific illustration. Be note it can be universally applicable to other countries as well. Malaysia has a high amount of biodiversity thanks to its tropical climate and a large population of over 30 million people. Malaysia has high temperatures and humidity, heavy rainfall, and a
The self-supervised learning has been widely used to refer to techniques that do not use human-annotated datasets to learn (visual) representations of the data (i.e. representation learning). Today we will discuss about a self-supervised learning system for pattern recognition by sensory integration. Artificial neural networks are useful tools for pattern recognition because they realize nonlinear
Will putting users in control of BYOI solve our privacy problem or BYOi privacy?. Let’s start from something everyone is familiar with, since it happens from time to time in the local news headline. A recent US journal report about 12 millions people’s location information being leaked, brings the headline for consumers to large privacy