Podcast
Questions and Answers
Sentiment analysis is the process of classifying whether a block of text is positive, negative, or, ______
Sentiment analysis is the process of classifying whether a block of text is positive, negative, or, ______
neutral
Sentiment analysis tries to gain is to be analyzed people’s opinions in a way that can help businesses ______
Sentiment analysis tries to gain is to be analyzed people’s opinions in a way that can help businesses ______
expand
Sentiment analysis focuses not only on polarity (positive, negative & neutral) but also on ______
Sentiment analysis focuses not only on polarity (positive, negative & neutral) but also on ______
emotions
Sentiment analysis uses various Natural Language Processing algorithms such as ______
Sentiment analysis uses various Natural Language Processing algorithms such as ______
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Sentiment analysis can be used to monitor product’s ______
Sentiment analysis can be used to monitor product’s ______
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Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can effectively generalize and thus perform tasks without explicit instructions. Recently, generative artificial neural networks have been able to surpass many previous approaches in performance.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can effectively generalize and thus perform tasks without explicit instructions. Recently, generative artificial neural networks have been able to surpass many previous approaches in performance.
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Machine learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine, where it is too costly to develop algorithms to perform the needed tasks.
Machine learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine, where it is too costly to develop algorithms to perform the needed tasks.
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The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods.
The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods.
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Data mining is a related (parallel) field of study, focusing on exploratory data analysis through unsupervised learning.
Data mining is a related (parallel) field of study, focusing on exploratory data analysis through unsupervised learning.
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ML is known in its application across business problems under the name predictive analytics. Although not all machine learning is statistically based, computational statistics is an important source of the
ML is known in its application across business problems under the name predictive analytics. Although not all machine learning is statistically based, computational statistics is an important source of the
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Study Notes
Sentiment Analysis
- Sentiment analysis classifies text as positive, negative, or neutral.
- The goal of sentiment analysis is to understand people's opinions to help businesses make informed decisions.
- Sentiment analysis examines not only the polarity (positive, negative, and neutral) of text but also the intensity and subjectivity of emotions.
Machine Learning
- Machine learning is a field of artificial intelligence that develops and studies statistical algorithms to perform tasks without explicit instructions.
- Machine learning has been applied to various areas, including large language models, computer vision, speech recognition, email filtering, agriculture, and medicine.
- Mathematical optimization methods provide the mathematical foundations of machine learning.
- Data mining is a related field that focuses on exploratory data analysis through unsupervised learning.
- Machine learning is known as predictive analytics when applied to business problems.
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Description
Test your knowledge of sentiment analysis with this quiz. Explore the basics and concepts of sentiment analysis, including its goal of classifying text based on expressed mood or mentality.
