Review of Various Applications of Machine Learning

Kunal S
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Abstract

— The usage of machine learning proposes an intelligent diagnostic study program that supports a web-based learning model aiming to develop students' ability to integrate information by allowing them to select study topics of interest, find information on those topics by searching online for related reading courseware and discussing what they have learned with their peers. The suggested learning program can effectively help students improve their knowledge while browsing online using the "webbased learning" approach, based on our test results. This study, on the other hand, proposes to use a machine-learning algorithm to anticipate future stock prices by combining open source libraries with pre-existing algorithms to help make this uncertain business model predictable. The result is entirely dependent on numbers and is predicted by many assumptions that may or may not occur in the real world, such as the forecast period. At the same time, the study also aims to provide a tool to anticipate accurate and timely traffic data. This fact has prompted us to pursue a solution to the problem of predicting traffic flow based on traffic data and models. Due to a large amount of available data for the transport system, it is difficult to accurately predict traffic flow.
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机器学习的各种应用综述
-机器学习的使用提出了一种智能诊断学习计划,该计划支持基于网络的学习模式,旨在培养学生整合信息的能力,允许他们选择感兴趣的学习主题,通过在线搜索相关阅读课件找到有关这些主题的信息,并与同龄人讨论他们所学的知识。根据我们的测试结果,建议的学习计划可以有效地帮助学生在使用“基于网络的学习”方法上网浏览的同时提高他们的知识。另一方面,这项研究建议使用机器学习算法来预测未来的股票价格,通过将开源库与已有算法相结合,帮助这种不确定的商业模式变得可预测。结果完全依赖于数字,并通过许多假设来预测,这些假设可能在现实世界中发生,也可能不发生,比如预测期。同时,该研究还旨在提供一种工具,以预测准确和及时的交通数据。这一事实促使我们寻求一种基于交通数据和模型预测交通流量问题的解决方案。由于交通系统的可用数据量很大,很难准确预测交通流量。
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