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Eager Learning and Lazy Learning in Machine Learning: A Comprehensive Comparison

Pickl AI

Support Vector Machines (SVM) : SVM is a powerful Eager Learning algorithm used for both classification and regression tasks. It constructs a hyperplane to separate different classes during training and uses it to make predictions on new data. Instance Similarity : Lazy Learning algorithms use a similarity measure (e.g.,

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From prediction to prevention: Machines’ struggle to save our hearts

Dataconomy

Several data mining and neural network techniques have been employed to gauge the severity of heart disease but the prediction of it is a different subject. Hybrid machine learning techniques excel in model selection by amalgamating the strengths of multiple models.

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[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.