Natural Language Processing
Artificial Intelligence AI
Artificial intelligence or AI is a widespread catchword that we have heard or read about. As we know it today, the concept of AI was birth out of The Dartmouth Conference of 1956 organized by Marvin Minsky, John McCarthy, and two other scientists from IBM. In 1970, AI was subjected to financial setbacks and limited computing power. Webster defined AI – 'as the capability of a machine to imitate intelligent human behavior'. AI describes a machine's ability to learn from information, create a degree of understanding, and then perform a task such as making decisions, assisting humans, and saving lives.
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Artificial intelligence is often talked about in conjunction with machine learning or deep learning and big data. Machine learning is a product of artificial intelligence (AI) that gives systems the ability to learn and improve without being trained routinely. Machine learning focuses on the development of computer codes that access data and use it to learn.
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Natural language processing (NLP), analytical studies can often approach using various methods. Furthermore, Script analysis at the individual level considers that 'from the early transactions between mother, father, and child, a life plan evolves. Script analysts work on the assumption that a person's behavior is partly programmed by the script, 'the life plan set down in early life.
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Why is AI such a scary thought? (Just hearing the phrase) Impact in implementing Machine language process automation
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Businesses can capitalize on societies' sentiment of Artificial Intelligence (AI), countless from improving the service level commitment to its customers and employees and process automation phase implementation. DATA COLLECTION AND DATA SET Dataset was obtained from Twitter using the "twitterscape package [1]". The dataset contains tweets 200 emphasizing the word AI and 'Artificial Intelligence' within their text. The data transformed before loading, which drop the following columns: URL, Html, likes, retweets, and the full name of the user. Only keep three columns user, timestamp, and text. Later, rename text to tweets and drop the user to prevent bias and maintain data integrity.
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