Decoding Natural Language Processing Training Ppt
These slides highlight various Natural Language Processing NLP techniques. These include grammar induction, sentiment analysis, aspect mining, name entity recognition, summarization, topic recognition, and speech-to-text conversion.
These slides highlight various Natural Language Processing NLP techniques. These include grammar induction, sentiment analy..
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Content of this Powerpoint Presentation
Slide 1
This slide lists Natural Language Processing techniques such as: grammar induction, sentiment analysis, aspect mining and name entity recognition.
Instructor Notes:
- Grammar Induction: It aids in the use of proper grammar when writing
- Sentiment Analysis: NLP is used to examine the sentence's positive and negative aspects
- Aspect Mining: Aspect mining is used in NLP to discover which aspects are favorable and which are bad
- Name Entity Recognition: It is used to recognize notable people's names, organizations, locations, and dates
Slide 2
This slide states a few of the Natural Language Processing techniques such as: Summarization, Topic Recognition and Speech to Text Conversion
Instructor Notes:
- Summarization: NLP may also summarize the content and offer the text's essence. It scores sentences based on their resemblance to other sentences
- Topic Recognition: NLP examines the text to determine the principal topic to which it is connected. It will extract certain keywords and organize them into categories
- Speech to Text Conversion: Speech to text enables machines to comprehend human language and interpret it with the intent of acting and responding in the same way that people do. The primary idea behind NLP is to feed human language as data to intelligent text-to-speech systems, which may subsequently be used in many fields
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