Sentiment Analysis Techniques in NLP: From Lexicon to Machine Learning Part 5 by Ayşe Kübra Kuyucu DataDrivenInvestor Similarly identifying and categorizing various types of offensive language is becoming increasingly important. For identifying sentiments and offensive language different pretrained models like logistic regression, CNN, Bi-LSTM, BERT, RoBERTa...

Unifying aspect-based sentiment analysis BERT and multi-layered graph convolutional networks for comprehensive sentiment dissection Scientific Reports One notable drawback lies in the subjective bias introduced by the algorithm. The bias of machine learning models stems from the data preparation phase, where a rule-based algorithm is employed...

A High-Level Guide to Natural Language Processing Techniques The method of read_csv() from the pandas' package converts the csv file into a pandas DataFrame. CommonLit provided Kaggle with the opportunity to develop algorithms that can help to aid administrators, teachers, parents, and students to understand how...

2 Artificial Intelligence AI Stocks to Buy Now and Hold For Decades The Motley Fool The General Problem Solver (GPS) cast planning as problem-solving used means-ends analysis to create plans. Graphplan takes a least-commitment approach to planning, rather than sequentially choosing actions from an initial state,...

Complete Guide to Natural Language Processing NLP with Practical Examples You can pass the string to .encode() which will converts a string in a sequence of ids, using the tokenizer and vocabulary. Language Translator can be built in a few steps using Hugging face’s transformers library....