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Linear Regression with Keras: A Practical Approach

Year: 2024

Type: conference-paper

Abstract: Regression analysis is a statistical method used to estimate the relationships between variables that exhibit cause-and-effect relationships. The primary focus of univariate regression is to analyze the relationship between a dependent variable and a single independent variable, formulating a linear equation that describes this relationship. In this paper we presents a practical approach to implementing a linear regression model using Keras, a high-level neural networks API built on TensorFlow.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14191045

Authors: Primbetov Abbaz Muratbay Uli, Jumaev Giyosjon Abdivahobovich

Language: English

Topic: Neural Networks and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6949615419

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