A Comprehensive Guide to Combining R and Python code for Data Science, Machine Learning and Reinforcement Learning

التفاصيل البيبلوغرافية
العنوان: A Comprehensive Guide to Combining R and Python code for Data Science, Machine Learning and Reinforcement Learning
المؤلفون: Navarro, Alejandro L. García, Koneva, Nataliia, Sánchez-Macián, Alfonso, Hernández, José Alberto
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Programming Languages
الوصف: Python has gained widespread popularity in the fields of machine learning, artificial intelligence, and data engineering due to its effectiveness and extensive libraries. R, on its side, remains a dominant language for statistical analysis and visualization. However, certain libraries have become outdated, limiting their functionality and performance. Users can use Python's advanced machine learning and AI capabilities alongside R's robust statistical packages by combining these two programming languages. This paper explores using R's reticulate package to call Python from R, providing practical examples and highlighting scenarios where this integration enhances productivity and analytical capabilities. With a few hello-world code snippets, we demonstrate how to run Python's scikit-learn, pytorch and OpenAI gym libraries for building Machine Learning, Deep Learning, and Reinforcement Learning projects easily.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2407.14695
رقم الأكسشن: edsarx.2407.14695
قاعدة البيانات: arXiv