An Artificial Neural Network (ANN) is a computational model inspired by the structure and functioning of the human brain. It consists of a network of interconnected nodes, called artificial neurons, that process input information and generate an output.
In an ANN, each artificial neuron receives one or more inputs and processes them using an activation function, which determines the neuron's output. The output of each neuron is transmitted to other neurons through weighted connections, which are used to adjust the contribution of each neuron to the final output.
During the training of an ANN, the model adjusts the weights of the connections between neurons to minimize the difference between the desired output and the actual output. This process is carried out using optimization algorithms, such as gradient descent.
ANNs are used in a wide variety of machine learning applications, such as image classification, natural language processing and time series prediction. They have also been used in complex problem solving, such as deep machine learning and the creation of recurrent and convolutional neural networks.
The financial sector is constantly implementing new technologies to modernize and digitize its functions. One of the reasons for this is the processing of [...]
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 »In the dynamic financial world, optimizing the return on available assets is essential to the success of any lender. Gam [...]
Read More »What is Digital Transformation? The industrial revolution profoundly changed the society of the 19th century, but the digital transformation of the [...]
Read More »Here you can edit your cookie preferences for this website.
Advertising cookies are used to deliver relevant advertisements and marketing campaigns to visitors. These cookies track visitors across all websites and collect information to deliver personalized advertisements.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as number of visitors, bounce rate, traffic source, etc.
Functional cookies help to perform certain functionalities such as sharing website content on social media platforms, collecting feedback and other third party features.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure the basic functionalities and security features of the website, anonymously.
Other non-categorized cookies are those that are being analyzed and have not yet been classified in a category.