Big Data Technology and Artificial Intelligence are like a pair of "sibling disciplines"—the former provides the fuel (data) for the latter, while the latter imparts wisdom (algorithms) to the former.

Overview: Building AI models begins with clear goals, clean data, and selecting appropriate algorithms.Beginners can use tools like Python, scikit-learn, and Te ...

Hands-on machine learning course with Python covering supervised learning (SVM, regression), unsupervised learning (K-Means, IRIS dataset), and deep learning (CNNs) using scikit-learn and TensorFlow.

The Least Squares Support Vector Machine (LS-SVM) is a modified SVM with a ridge regression cost function and equality constraints. It has been successfully applied in many classification problems.

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

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However, the major drawback of SVM is its higher computational burden for the constrained optimization programming. This disadvantage has been overcome by least squares support vector machines (LS-SVM ...

4. Support Vector Regression Learning Methods Support Vector Machines for Regression (SVRs) share the same advantages and disadvantages as SVMs. That means, SVMs training methods can be extended to ...