We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

The rapid development of deep learning in recent years is largely due to the rapid increase in the scale of data. The availability of large amounts of data is revolutionary for model training by the ...

The field of machine learning includes the development and application of computer algorithms that improve with experience. Machine learning methods can be divided into supervised, semi-supervised and ...

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...

The recently published 2025 Machine Learning Emotional Footprint Report from global IT research and advisory firm Info-Tech Research Group highlights the top machine learning platforms that help organ ...

OpenAI's ChatGPT system has sent the topic of artificial intelligence through the roof. But so many professionals across industries, including healthcare, do not truly understand how AI works – ...

Even though the buzz around neural networks, artificial intelligence, and machine learning has been relatively recent, as many know, there is nothing new about any of these methods. If so many of the ...

Sean Cusack has been a backyard beekeeper for 10 years and a tinkerer for longer. That’s how he and an entomologist friend got talking about building an early warning system to alert hive owners to ...

Artificial intelligence (AI) machine learning is a powerful tool for its predictive capabilities in finding tiny needles of meaningful patterns in large haystacks of real-world data. From this vantage ...

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world. Machine-learning algorithms are responsible for the vast majority of the artificial intelligence ...