technotes.

  Fundamental Tasks of NLP:  Sentiment Analysis: Sentiment analysis is a natural language processing (NLP) technique used to determine the sentiment expressed in a piece of text. The goal of sentiment analysis is to automatically extract and quantify subjective information from text data such as opinions, attitudes, emotions and feelings. Let's say we have a dataset containing customer reviews of a product, and we want to analyze the sentiment expressed in each review. The sentiment could be positive, negative or neutral. For example, given the review " I absolutely love this product! It's amazing! ", the sentiment analysis model might classify it as positive . Similarly, for the review " This product is terrible. I would not recommend it to anyone. ", the model might classify it as negative . And for the review " The product arrived on time, but it was not what I expected. ", the model might classify it as neutral . Steps of Sentiment Analy...

    Natural Language Processing is a subfield of AI that focuses on the interaction between computers and human languages. The primary goal of NLP is to enable machines to understand, interpret, and generate human language in a way that is both meaningful and valuable. NLP in AI involves the development of algorithms and models that allow computers to process and analyze natural language data. This includes tasks such as text parsing, sentiment analysis, language translation and speech recognition. NLP applications can be found in various domains, including virtual assistants, chatbots, language translation services and sentiment analysis tools.  Tasks of NLP :   Text Classification: Sentiment Analysis: Determining the sentiment expressed in a piece of text (positive, negative, neutral). Topic Classification: Categorizing a document or piece of text into predefined topics or categories. Named Entity Recognition (NER): Identifying and classifying entiti...