Page 113 - TP_Modular_V2.1_Class8
P. 113

Artificial Intelligence






                                 Data                  Natural Language Processing          Computer Vision



                 NATURAL LANGUAGE PROCESSING (NLP)

                 Natural Language Processing (NLP) is a subfield

                 of AI which helps in communication between
                 human and computer in natural language. It
                 enables a computer to read and understand

                 data by mimicking human natural language.
                 NLP is used for a variety of tasks such as email
                 filters. For example, a lot of people receive a

                 lot emails which are useless. NLP checks the
                 sender of the email and categorises the mails
                 as spam or junk. NLP also finds its use in the autocomplete and spell-check feature of word processors. NLP also

                 proves to be quite useful in voice text messaging and virtual assistants.                                   Artificial Intelligence
                                                             DATA

                                                             Data refers to raw facts and figures that are processed and

                                                             analysedo find meaningful insights. Data plays a pivotal role in
                                                             the field of AI. Data collection is the process of gathering and
                                                             sourcing information from numerous origins, including sensors,
                                                             databases, and online sources.

                                                             The quality of data is crucial for AI applications. For effective

                                                             AI performance, data must be accurate, relevant, complete,
                                                             and free from errors. The accuracy of AI outcomes is heavily
                                                             dependent on the quality of the data provided. Thus, data can
                                                             be considered the lifeblood of AI: an AI system relies on high-
                 quality, well-structured data to learn and make predictions. Providing incomplete, incorrect, or low-quality data

                 will lead to flawed, inaccurate, or unreliable results.

                 Data types can include numerical values (such as temperature, loan amount, etc.), categorical data (such as
                 gender, cocolourc.), or even unstructured text data (like doctor’s notes, prescriptions, opinion surveys, etc.).







                                                              The AI Corner! (AI— Domains and Advantages)        111
   108   109   110   111   112   113   114   115   116   117   118