Deep Learning, is a more evolved branch of machine learning, and uses layers of algorithms to process data, and imitate the thinking process, or to develop abstractions. It is often used to visually recognize objects and understand human speech. Information is passed through each layer, with the output of the previous layer providing input for […]
Machine Learning vs. Deep Learning
The debate on machine learning vs. deep learning has gained considerable steam in the past few years. The fundamental strength of both these technologies lies in their ability to learn from available data. Though both of these offshoot AI technologies triumph in “learning algorithms,” the manner in which machine learning (ML) algorithms learn is very […]
Deep Learning Demystified
The “deep” in deep learning refers to the number of hidden layers involved in the design. Deep learning is a way of training artificial intelligence (AI) to recognize specific data, such as speech or faces, and to make predictions based on previous experiences. Unlike machine learning, which organizes and sends data through predefined algorithms, deep […]
Artificial Neural Networks: An Overview
Neural networks and deep learning currently provide some of the most reliable image recognition, speech recognition, and natural language processing solutions available. However, it wasn’t always that way. One of the earliest and simplest teaching philosophies for artificial intelligence was marginally successful. It suggested that loading the maximum amount of information into a powerful computer […]
Deep Learning and Machine Learning Differences: Recent Views in an Ongoing Debate
The science of Machine Learning (ML) has been around since the 1970s, but low horsepower processors and limited data forced the progress of Machine Learning to slow down in the 1980s. Ever since Big Data has enabled the use of unlimited “variety, volume, and velocity” business data, Machine Learning resurfaced as a powerful game changer […]