Some of the earliest-used machine learning algorithms, such as decision trees, produced systems of hard if-then rules similar to existing hand-written rules. The cache language models upon which many speech recognition systems now rely are examples of such statistical models. Text analytics converts unstructured text data into meaningful data for analysis using different linguistic, statistical, https://metadialog.com/ and machine learning techniques. Analysis of these interactions can help brands determine how well a marketing campaign is doing or monitor trending customer issues before they decide how to respond or enhance service for a better customer experience. Additional ways that NLP helps with text analytics are keyword extraction and finding structure or patterns in unstructured text data. We want to build models that enable people to read news that was not written in their language,…