Data Science & Machine Learning in Website Development
Km Apoorva shriwastawa Manjeet Singh Dipesh Yadav
This research paper explores the integration of data science and machine learning techniques into web development practices. With the increasing demand for data-driven and personalized web experiences, the utilization of advanced technologies becomes imperative. The paper investigates the application of tools and libraries such as TensorFlow.js, Scikit-learn.js, D3.js, Pandas.js, and Chart.js for implementing data analysis, predictive modelling, and visualization within web applications. Through an examination of case studies and practical implementations, the paper highlights the benefits and challenges of incorporating data science and machine learning into web development projects. Additionally, it provides insights into the future trends and potential advancements in this interdisciplinary field. The findings of this research aim to guide developers, researchers, and practitioners in harnessing the power of data science and machine learning to enhance web development practices and create more intelligent and adaptive web applications.
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Quantam Computing Publication