Abstract

This research explores the utilization of machine learning and deep learning methods for analyzing business data in the context of internal s. With the exponential growth of data in businesses, the extraction of insights and informed decisionmaking based on data has become crucial. Machine learning algorithms offer effective tools for identifying patterns and trends within large datasets. This article delves into various machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and deep learning, and investigates their applications in business data analytics. Notably, machine and deep learning models such as Support Vector Machine (SVM) and Decision Tree (DT) prove highly valuable in analyzing complex datasets such as text and images. Moreover, the paper evaluates the challenges associated with implementing machine learning models, such as data preprocessing, model selection, and performance evaluation. Lastly, the paper concludes by discussing potential future research directions in the field of business data analytics, emphasizing the utilization of machine learning and deep learning techniques within the realm of internal.

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