ML & Deep Learning

Machine learning means computers learn from data using algorithms to perform a task without being explicitly programmed. Deep learning uses a complex structure of algorithms modeled on the human brain. This enables the processing of unstructured data such as documents, images, and text.

From a business point of view, both technologies complement each other and are often used to solve a business problem.

Machine Learning

Machine learning is an intersection between computer science, statistics, and artificial intelligence which allows computers to learn specific tasks and improve automatically without being explicitly programmed.
It refers to a branch of artificial intelligence wherein computers have the ability to recognize patterns in data and use what they’ve learned to make predictions on new, unseen data.
There are two main types of machine learning problems: supervised and unsupervised. In general, the learning process of these algorithms can either be supervised or unsupervised depending on the data they’re using to feed their training models.

Deep Learning

Deep learning is a subset of machine learning in which neural networks are more complex.
Deep learning models typically consist of a layered structure of algorithms called an artificial neural network.
Deep learning demands huge datasets but does not need much human intervention for it to work properly.
Transfer learning is an excellent solution when you don’t have enough data to train a model and you still want it to work well in your application.