What is Deep Learning?
Deep learning is a subset of machine learning that deals with algorithms inspired by the structure and function of the brain, known as artificial neural networks. Neural networks are made up of interconnected nodes, or layers of neurons, that can learn to recognize patterns in input data. The learning process of a neural network is like that of a child, who gradually learns to recognize patterns through experience.
Deep learning algorithms can learn from unstructured and unlabeled data, such as images, sounds, and text. This is in contrast to traditional machine learning algorithms, which require data to be labeled and structured in order to learn from it. Deep learning algorithms can learn directly from data without human supervision. Deep learning has achieved impressive results in a variety of tasks, such as image classification, object detection, and natural language processing. Deep learning is responsible for recent breakthroughs in artificial intelligence (AI).
How deep learning works
Computer programs that use deep learning go through the same process as a child learning to recognize a dog. Each algorithm in the hierarchy applies a non-linear transformation to its inputs and uses what it learns to build a statistical model as an output. The iteration continues until the output reaches an acceptable level of accuracy. The number of processing layers through which the data must pass is what drives the depth of the label.
In traditional machine learning, the learning process is supervised, and the programmer has to be extremely specific when telling the computer what kinds of things it should be looking for in an image to decide whether it contains a dog or not. This is a laborious process called feature extraction, and the success rate of the computer depends entirely on the programmer’s ability to accurately define the feature set for the dog. The advantage of deep learning is that the program builds the set of features on its own without supervision. Unsupervised learning is not only faster, but it is also generally more accurate.
Top 10 Deep Learning Tools
2. Microsoft Cognitive Toolkit