Differences between training dataset and testing dataset

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Reference no: EM133456290

Question

Businesses leverage on artificial intelligence to understand customer patterns, behaviors in depth and to predict some business actions. Machine learning is a component of artificial intelligence to comprehend big data, characteristics, building methods and associate relationship within the massive data structure. Data analysis acquired through machine learning. Machine learning algorithms build a model based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to do so. This has been used in the filed of medicine, logistic, marketing, manufacturing, agriculture just to name a few.

(a) Explain the differences between training dataset and testing dataset, and why they are important in the cross-validation process.

(b) Based on typical scenario in your workplace or business, identify OPPORTUNITY where you can use data analytics to improve operations, business, or process. Explain the current problem and how data analytics, and the manner data visualization assist in solving problems.

Reference no: EM133456290

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