The article discusses nine different Natural Language Processing (NLP) algorithms that are widely used in real-world solutions currently. These include Tokenization, Sentiment Analysis, Named Entity Recognition, Topic Modeling, Text Summarization, Semantic Analysis, Clustering, and Text Analysis. The text also provides a brief overview of the underlying concepts and steps involved in each algorithm. Python is used for development and Jupyter Notebooks are employed for writing the code.