Deep learning is a branch of machine learning that relies on multi-layered artificial neural networks to learn and extract features from data. Unlike conventional machine learning, which relies on algorithms that require features to be defined manually, deep learning allows models to learn autonomously from raw data.
The artificial neural networks used in deep learning are composed of multiple layers of interconnected neurons, each of which processes a portion of the data and the extracted features are used in subsequent layers to extract more complex features. This process is repeated at each layer until the most abstract features are extracted from the dataset.
Deep learning is used in a variety of applications, such as computer vision, natural language processing, machine translation, fraud detection, object identification, among others. Due to its ability to learn autonomously and its high accuracy in identifying complex patterns in data, deep learning has become a powerful tool in the field of artificial intelligence and machine learning.
Reference: Yoshua Bengio. Learning Deep Architectures for AI.
Chargeback refers to refunds that occur when, at the request of a cardholder, the bank requests a refund on his or her behalf [...].
Read More »Churn, or customer churn rate, is a constant challenge for today's businesses. The ability to retain customers is a constant challenge for today's companies.
Read More »The use of Artificial Intelligence in business is becoming more and more common and necessary for the optimization and evolution of processes. In one of our [...]
Read More »Artificial intelligence is changing the world at breakneck speed and you're probably wondering when it will surpass artificial intelligence in the [...]
Read More »
