There are numerous real-world use cases where the number of features available that may potentially be used to train a model is very large. A common example is economic data, and using its constituent stock price data, employment data, banking data, industrial data, and housing data together to predict the gross domestic product (GDP). Such types of data are said to have high dimensionality. Though they offer numerous features that can be used to model a given use case, high-dimensional datasets increase the computational complexity of machine learning algorithms, and more importantly may also result in over fitting. Over fitting is one of the results of the curse of dimensionality, which formally describes the problem of analyzing data in high-dimensional spaces (which means that the data may contain many attributes, typically hundreds or even thousands...
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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.
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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