Artificial Intelligence in Greenhouses
Machine Learning
Machine learning (ML) is a branch of AI that focuses on using data to determine patterns and correlations and discover knowledge from datasets, gradually improving its accuracy. This is a complicated way of saying the machine learns from the given data without being explicitly programmed. Machine learning is dedicated to establishing algorithms and methods that will allow computers to learn from data and improve without requiring explicit programming. By iteratively examining historical data, these models identify patterns and enhance their precision as time progresses. The typical process involves training the model on a dataset to uncover correlations between input features and output values. The process in which a computer can “learn” from data without being programmed and adjust to new inputs to accomplish specific tasks (e.g., self-driving robots) is described as machine learning.
Machine Learning Algorithms
Several prevalent ML algorithms have emerged within the context of agriculture. Machine learning algorithms can ingest vast amounts of data and identify complex patterns that humans would struggle to discern. These models can predict future conditions, such as the likelihood of disease outbreaks or optimal harvest times, based on historical and real-time data.
Deep Learning
Deep Learning. Deep learning is another subset of AI and, more specifically, a subset of machine learning that uses multilayered neural networks, sometimes called deep neural networks. It is developed to mimic the information process system of the human or animal brain, which enables one to learn and make decisions with little intervention.
Types of Deep Learning Algorithms
Deep learning algorithms are incredibly complex, and there are different types of neural networks to address specific problems or datasets. Each has its advantages, and they are presented here roughly in the order of their development, with each successive model adjusting to overcome a weakness in a previous model.
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