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Answer: Identifying the problem type (e.g., classification, regression, clustering) to apply the correct machine learning approach, The methods and sources for collecting relevant sales data, including considerations for data quality and completeness
When defining a machine learning problem, especially in a scenario like forecasting sales for a retail company, the most critical factors include identifying the correct problem type (e.g., regression for predicting continuous numerical values like sales) and ensuring the data collection methods are robust to guarantee high-quality, relevant data. While UI/UX design (A) and database administration (C) are important in broader project contexts, they are not directly relevant to the initial problem definition phase in machine learning. Option E is incorrect because not all listed options are critical for defining the ML problem.
Author: LeetQuiz Editorial Team
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As a Google Cloud Professional Machine Learning Engineer tasked with developing a predictive model for a retail company to forecast sales, what are the key factors you should consider when defining the machine learning problem? The solution must optimize for accuracy while adhering to a tight budget and ensuring scalability for future data growth. Choose the two most critical factors from the options provided.
A
The aesthetic design of the user interface for the sales dashboard
B
Identifying the problem type (e.g., classification, regression, clustering) to apply the correct machine learning approach
C
The efficiency of the database queries used to retrieve historical sales data
D
The methods and sources for collecting relevant sales data, including considerations for data quality and completeness
E
All of the above
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