Aspect-based sentiment analysis is advanced text analysis technique, which helps you get the most out of your data. Tutorial how to do it with MonkeyLearn.
Aspect Based Sentiment Analysis, PyTorch Implementations
Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF - soujanyaporia/aspect-extraction
In this article, the author explored vocabulary and phrase matching using the spaCy library. This tutorial is showing how to create rule based and phrase based matching
In this article machine learning is applied for customer churn prediction problem. The Kaggle dataset with 14 columns (some of them are categorical) is used. Random Forest algorithm was selected as machine learning approach for customer churn problem.
The article is showing inner workings of Multinomial Naive Bayes algorithm that is used for chatbot. You can find also links to articles that are covering some others algorithms.
Here you will learn anatomy of chatbot and different approaches used to build chatbots. Also machine learning techniques such as TF-IDF, Cosine Similarity is covered to show how to implement chatbot with python
NLP model that can assist customer support agents by suggesting previously-asked, similar questions. Universal sentence encoder (USE) from tfhub is used.
Tutorial how to build a simple chatbot using attention, RNN, python and TensorFlow
The post is showing how to build chatbot using machine learning techniques such as Elasticsearch (basically TF-IDF) , Doc2Vec .
Using machine learning to create programs that can automatically write or modify programming code
Full working example how to use TF-IDF and scikit-learn to extract important keywords from documents. Stack Overflow dataset
Tutorial how to build RASA Chatbot that can detect user intent and respond to user. Very comprehensive guide.
The author explained how to build chatbot using nltk.chat.util: Chat. This is a class that has all the logic that can be used by the chatbot.