یادگیری ماشین نظارت شده برای تحلیل متن در آر

دسته: هوش مصنوعی
یادگیری ماشین نظارت شده برای تحلیل متن در آر

سال انتشار: 2021  |  402 صفحه  |  حجم فایل: 16 مگابایت  |  زبان: انگلیسی

Supervised Machine Learning for Text Analysis in R (Chapman & Hall/CRC Data Science Series)
نویسنده:
Emil Hvitfeldt, Julia Silge
ناشر:
Chapman and Hall-CRC
ISBN10:
0367554186
ISBN13:
9780367554187

 

قیمت: 12000 تومان

خرید کتاب توسط کلیه کارت های شتاب امکان پذیر است و بلافاصله پس از خرید، لینک دانلود فایل کتاب در اختیار شما قرار خواهد گرفت.

برچسب‌ها:  یادگیری ماشین  

عناوین مرتبط:


Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are. 


ارسال دیدگاه


 (الزامی)  (الزامی)
ایمیل شما نزد مدیر سایت محفوظ بوده و برای عموم نمایش داده نخواهد شد.