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.
Machine learning model such as average word embeddings (AWE) is used to retrieve relevant CVs based on job description. Principal Component Analysis (PCA) as a reduction technique is also utilized.
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 .
Article about different neural network architectures. It includes also section about Neural Programmer - application of neural net for programming tasks
Using machine learning to create programs that can automatically write or modify programming code
How to build simple text classification model to predict tag. Training, evaluation, prediction and building confusion matrix is covered.
Full working example how to use TF-IDF and scikit-learn to extract important keywords from documents. Stack Overflow dataset
The author applied machine learning for automatic tagging documents before saving in Pocket application.
Showcase of fitness tracker data analysis. Nice data visualization with interactive and animated plots in R.
Several techniques with detailed explanation and code are proposed for anomaly detection
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.
A curated list of applied machine learning and data science notebooks and libraries accross different industries.
Creating a dialogue chat bot, which is able to:
Answer programming-related questions (using StackOverflow dataset)
Chit-Chat and simulate dialogue on all non-programming related questions
Series on creating a chatbot with the RASA stack as a newbie