This is the sixth article in my series of articles on Python for NLP. In my previous article, I talked about how to perform sentiment analysis of Twitter data using Python's Scikit-Learn library. In this article, we will study topic modeling, which is another very important application of NLP. We
This is the fifth article in the series of articles on NLP for Python. In my previous article, I explained how Python's spaCy library can be used to perform parts of speech tagging and named entity recognition. In this article, I will demonstrate how to do sentiment analysis using Twitter
Classification is a large domain in the field of statistics and machine learning. Generally, classification can be broken down into two areas:
Binary classification, where we wish to group an outcome into one of two groups.
Multi-class classification, where we wish to group an outcome into one of multiple
Text classification is one of the most important tasks in Natural Language Processing. It is the process of classifying text strings or documents into different categories, depending upon the contents of the strings. Text classification has a variety of applications, such as detecting user sentiment from a tweet, classifying
A typical machine learning process involves training different models on the dataset and selecting the one with best performance. However, evaluating the performance of algorithm is not always a straight forward task. There are several factors that can help you determine which algorithm performance best. One such factor is