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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 is also used in the autocomplete and spell-check feature of word processors. NLP
                 also proves to be quite useful with voice text messaging and virtual assistants.





















                    DATA

                 Data refers to raw facts and figures that are processed and analyse to 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, colour, etc.), or even unstructured text data
                 (like doctor’s notes, prescriptions, opinion surveys, etc.).

                    COMPUTER VISION (CV)

                 Computer Vision is a very popular field of AI that trains a computer to understand and  interpret

                 the visual world. Human vision starts at the “eyes” but machine uses digital images from a camera
                 for vision. Deep learning models and machines accurately identify and classify objects that act
                 according to what they see, using digital images from camera.
                 According to Fei-Fei Li, Computer Vision is defined as “a subset of mainstream artificial intelligence
                 that deals with the science of making computers or machines visually enabled, i.e., they can

                 analyse and understand an image.”


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