Popular AI Models: A Complete Guide for Beginners and Experts

The world is changing rapidly; every industry is moving toward digitization and automation, and Artificial Intelligence is playing a significant role in this change. We are seeing the reshaping of the IT and development industry, where AI is doing the majority of tasks, and there is no role for unproductive and repetitive tasks. In the realm of fast-changing scenarios, it is important to learn about AI and integrate it into your business processes to boost productivity and achieve the best possible results. So, in this post, we will discuss some popular AI models that will help you to integrate AI into your business processes.

Top 5 Most Popular AI Models In Businesses

1. Decision Trees (DT) Model

Decision Trees are a well-known machine learning model used for multiple purposes, such as classification and regression tasks. This model splits the data into subsets and classifies them based on inputs and features, making a tree-like structure for precise decisions. The structure of a decision tree consists of nodes, branches, and leaves. The former one represents the features, the next one represents decision rules, and the last one represents outcomes.

2. Linear Regression (LR) Model

It is a data analysis technique that predicts the future outcome by accessing the past data. This AI model is specially developed to establish a connection between the two sets of data by accessing their previous connection. As the name suggests, this AI model forms a linear equation and predicts the future outcome based on historical data. For example, an e-commerce company can expect sales value during an offer period by accessing the data of earlier shopping trends during the same period.

3. K-Nearest Neighbors Model

K-Nearest Neighbors (KNN) is a powerful and simple non-parametric classification and regression algorithm that classifies data based on their classes. The classification is done on the basis of neighbors in the feature space. The calculation done by this model is simple to understand, as the distance between a point and its 𝑘 is measured. It is a commonly used machine learning technique, preferred by developers because of its simplicity and ease of usage.

4. Naive Bayes (NB) Model

The naive Bayes (NB) model is based on Bayes’s Theorem; it is a probabilistic classification model which calculates the probability of something accessing the input given by the users. This model works on the assumption that features are independent, which makes computations simple; it is an efficient and scalable mode, widely used in spam detection and sentiment analysis applications. Well! This AI model delivers solid performance, and its uncomplicated assumptions don't limit the potential of this model.

5. Logistic Regression (LogR) Model

Logistic Regression is the most suitable AI model for binary calculations. In this model, the outcome can be of two types, such as Yes/No, Profit/Loss, and more. It assesses the probability of some instances and predicts them scientifically. This AI model uses probability estimation and logic functions to operate and provide helpful information to its users.

Conclusion

Today, AI models are a driving factor in the IT industry; it has become vital for businesses to implement them and develop processes for productive outcomes. If one is not using AI models in their business, it will make them less competitive in the market. As using AI models has many benefits, the internet is filled with numerous AI models; in this post, we shared the top 5 AI models to use in your business process; we hope that you found this helpful post and that it will help you to select the right AI model for your business.