Let's now apply these feature transformers and feature extractors to a very modern real-world use case—sentiment analysis. In sentiment analysis, the goal is to classify the underlying human sentiment—for example, whether the writer is positive, neutral, or negative towards the subject of a text. To many organizations, sentiment analysis is an important technique that is used to better understand their customers and target markets. For example, sentiment analysis can be used by retailers to gauge the public's reaction to a particular product, or by politicians to assess public mood towards a policy or news item. In our case study, we will examine tweets about airlines in order to predict whether customers are saying positive or negative things about them. Our analysis could then be used by airlines in order to improve...
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You're reading from Machine Learning with Apache Spark Quick Start Guide
Jillur Quddus is a lead technical architect, polyglot software engineer and data scientist with over 10 years of hands-on experience in architecting and engineering distributed, scalable, high-performance, and secure solutions used to combat serious organized crime, cybercrime, and fraud. Jillur has extensive experience of working within central government, intelligence, law enforcement, and banking, and has worked across the world including in Japan, Singapore, Malaysia, Hong Kong, and New Zealand. Jillur is both the founder of Keisan, a UK-based company specializing in open source distributed technologies and machine learning, and the lead technical architect at Methods, the leading digital transformation partner for the UK public sector.
Read more about Jillur Quddus
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Jillur Quddus is a lead technical architect, polyglot software engineer and data scientist with over 10 years of hands-on experience in architecting and engineering distributed, scalable, high-performance, and secure solutions used to combat serious organized crime, cybercrime, and fraud. Jillur has extensive experience of working within central government, intelligence, law enforcement, and banking, and has worked across the world including in Japan, Singapore, Malaysia, Hong Kong, and New Zealand. Jillur is both the founder of Keisan, a UK-based company specializing in open source distributed technologies and machine learning, and the lead technical architect at Methods, the leading digital transformation partner for the UK public sector.
Read more about Jillur Quddus