مروری اجمالی بر یادگیری ماشین: فرآیند، الگوریتم ها، نحوه انتخاب الگوریتم، کاربردها، مزایا و چالش های آن

محورهای موضوعی : مدیریت

امل سیاح ¹ , امیر عباس شجاعی ^{2 *} , علی علی اکبری ³ , مهدی حاجی رضایی ⁴ , حمید توحیدی ⁵

1 - دانشجوی دکتری مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
2 - دانشیار گروه مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران (نویسنده مستول).
3 - استادیار گروه مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
4 - استادیار گروه مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.
5 - دانشیار گروه مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران.

تاریخ دریافت : 1403/12/21 تاریخ پذیرش : 1404/05/27 تاریخ انتشار : 1404/07/14

کلید واژه: یادگیری ماشین, هوش مصنوعی, فرایند یادگیری ماشین, الگوریتم های یادگیری ماشین,

چکیده مقاله :

الگوریتم‌های یادگیری ماشینی مدل‌های محاسباتی هستند که به رایانه‌ها اجازه می‌دهند الگوها را بفهمند و بدون برنامه‌نویسی صریح بر اساس داده‌ها، پیش‌بینی یا تصمیم گیری کنند. این الگوریتم‌ها شالوده هوش مصنوعی مدرن را تشکیل می‌دهند و در کاربردهای مختلفی از جمله تشخیص تصویر و گفتار، پردازش زبان طبیعی، سیستم‌های توصیه، تشخیص تقلب، خودروهای خودران و غیره استفاده می‌شوند. این مطالعه با هدف مروری اجمالی بر یادگیری ماشین به ارائه یک نمای کلی از توسعه یادگیری ماشینی تا امروز می پردازد و سپس فرآیند یادگیری ماشین، الگوریتم‌های مختلف آن، روش انتخاب الگوریتم ها را مورد بحث قرار می دهد. همچنین به کاربردها، چالش‌ها و مزایای یادگیری ماشین اشاره می شود. به طور کلی، این مقاله قصد دارد به عنوان یک نقطه مرجع برای متخصصان دانشگاهی، صنعت و همچنین برای تصمیم‌گیرندگان در موقعیت‌های مختلف دنیای واقعی و حوزه‌های کاربردی، مورد استفاده قرار گیرد. روش تحقیق حاضر مبتنی بر تجزیه و تحلیل کیفی است که در آن ادبیات مختلف براساس موضوع یادگیری ماشین مورد بررسی قرار گرفته است. نتایج نشان می دهد که یادگیری ماشین برای ایجاد تحول بزرگ در فناوری آماده است و یکی از سریع‌ترین فناوری‌هایی است که تا امروز مورد استفاده بوده است و به طور مداوم در حال تکامل است، یادگیری ماشین یک فناوری با ریسک و بازده بالا می باشد.

چکیده انگلیسی:

Machine learning algorithms are computational models that allow computers to understand patterns and make predictions or decisions based on data without explicit programming. These algorithms form the foundation of modern artificial intelligence and are used in various applications such as image and speech recognition, natural language processing, recommender systems, fraud detection, and autonomous vehicles. This study aims to provide a brief overview of machine learning by discussing the development of machine learning to date and then examining the machine learning process, its various algorithms, and the method of selecting algorithms. It also addresses the applications, challenges, and benefits of machine learning. Overall, this paper intends to serve as a reference point for academic and industry professionals as well as for decision-makers in various real-world situations and application domains. The present research methodology is based on qualitative analysis in which various literature based on machine learning is reviewed. The results show that machine learning is poised to create a major technological revolution and is one of the fastest-growing technologies used to date, and it is constantly evolving. Machine learning is a high-risk, high-reward technology.

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