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Explain the steps you typically take for data wrangling and cleaning prior to applying machine learning algorithms?

Data Scientist

Palantir Technologies

Netflix

Microsoft

Honeywell

Headspace

Curve

Explain the steps you typically take for data wrangling and cleaning prior to applying machine learning algorithms?
How do you ensure data cleanliness before feeding it into a machine learning model?
What are the typical steps you follow when wrangling and cleaning data for machine learning applications?
Could you describe the process you go through to ensure high-quality data for machine learning models?
How do you approach cleaning and restructuring data to optimize its use in machine learning?
Please explain the steps you take to turn raw data into something that a machine learning algorithm can interpret.
What are some of the prerequisites for clean data when it comes to machine learning, and how do you ensure they are all met?
Before applying machine learning algorithms, what are some of the things you have to do in terms of data wrangling and cleaning?
How do you ensure that the data you are feeding into machine learning algorithms is representative and unbiased?
Could you walk me through the typical workflow you follow when cleaning and preparing data for use in machine learning models?
Can you walk me through the process you take to prepare data for machine learning algorithms?

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Interview question asked to Data Scientists interviewing at New Relic, Microsoft, Thumbtack and others: Explain the steps you typically take for data wrangling and cleaning prior to applying machine learning algorithms?.

Explain the steps you typically take for data wrangling and cleaning prior to applying machine learning algorithms?

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