Principal component analysis and singular value decomposition are among the two common concepts of linear algebra in machine learning. After collecting raw data, is...
Activate function is an essential element for designing a neural network. Choosing the activation function will give you complete control over the network model’s...
Confounding variable is a statistical term.The concept is a bit confusing for many people because of the method to use. For starters, different researchers...
The classification process helps with the categorization of the dataset into different classes. A machine learning model enables you to: Frame the problem, Collect...
Every machine learning algorithm analyzes and processes input data and generates the outputs. The input data includes features in columns. These columns are structured...
This article will discuss how SMOTE module helps increase underrepresented numbers in the dataset of a machine learning model. SMOTE is the best method...
In this article, you will learn about generative adversarial networks or GANs. Generative adversarial networks are the generative modeling approach for deep learning techniques....
As the datasets increase drastically, we are developing skills to enhance the way we train deep neural networks. This helps data scientists map the...
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