Artificial neural networks are considered one of the most important and most advanced sciences at the present time, and they have many applications in various sciences. They also have their own specialized experts.
I would say that the data collection for ANNs involves several methods such as:
Surveys and Questionnaires: Gathering data through structured surveys or questionnaires to obtain specific information.
Sensors and IoT Devices: Collecting data from sensors embedded in devices or Internet of Things (IoT) devices, such as temperature sensors or wearable devices.
Web Scraping: Extracting data from websites or online sources using automated scripts or tools.
Databases and Data Repositories: Accessing existing datasets stored in databases or data repositories, such as government databases or research repositories.
User Interactions: Collecting data through user interactions, such as clickstream data or user behavior on websites or mobile apps.
Data Logs: Collecting data from system logs, server logs, or application logs that record various events or actions.
Social Media and Online Platforms: Gathering data from social media platforms, online forums, or public APIs.
Manual Data Entry: Entering data manually into a system or database.
Artificial Neural Networks contain artificial neurons which are called units. These units are arranged in a series of layers that together constitute the whole Artificial Neural Network in a system. A layer can have only a dozen units or millions of units as this depends on how the complex neural networks will be required to learn the hidden patterns in the dataset. Commonly, Artificial Neural Network has an input layer, an output layer as well as hidden layers. The input layer receives data from the outside world which the neural network needs to analyze or learn about. Then this data passes through one or multiple hidden layers that transform the input into data that is valuable for the output layer. Finally, the output layer provides an output in the form of a response of the Artificial Neural Networks to input data provided.
Artificial Neural Networks (ANNs) have found numerous modern applications across various fields. Some of the key areas where ANNs are commonly used include:
*. Image and Speech Recognition *. Natural Language Processing (NLP)
*. Recommendation Systems
*. Financial Analysis and Forecasting
*. Healthcare and Medicine
*. Autonomous Vehicles:
The mechanism of data collection for ANNs depends on the specific application and available data sources. Some common methods include:
*. Structured Databases
*. Web Scraping: Data can be collected by scraping information from websites or online sources. Web scraping involves extracting data from web pages using automated tools or scripts.