In the previous 4 blog posts, I covered the most important steps of the NLP Pipeline, data collection, text preprocessing, feature extraction, and modeling. In this blog post, I will go over the last and most important stage, model evaluation. Model evaluation is vital to understanding how effective...

In the previous blog post about modeling, I covered traditional machine learning algorithms in NLP. Recent developments in artificial intelligence have led to the emergence of a new field called deep learning. Deep learning is a subset of machine learning that utilizes neural networks that mimic the...

In the previous blog post, I covered feature extraction, the second step in the NLP Pipeline. In this post, I will go over modeling, the most complex stage in the NLP process.  The first step in modeling is choosing between using a traditional machine learning algorithm or deep learning. That determination...

In the previous blog post, I covered text preprocessing as the first step in the NLP Pipeline. In this post, I will cover the following step,  feature extraction. Feature extraction, a form of data manipulation, is the last step before building the actual NLP model. Feature extraction essentially aims...

The process of transforming raw text into a natural language processing (NLP) model that can translate text between numerous languages or generate paragraphs of human-sounding text, involves a multitude of complex stages known together as the NLP Pipeline. These include data collection, text preprocessing,...

There are over about 7,000 languages spoken around the world today. However, over 40% of them are endangered and may soon be lost. Meta has proposed a series of AI models that could help preserve language diversity and provide robust NLP tools that benefit those who speak underrepresented languages called...