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1
- Video overview & format
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- Introductory Behavioral questions | Data science interview
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- Social media platform bot issue task overview | Data science interview
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- What are some features we should investigate regarding the bot issue? | Data science interview
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- Classification model implementation details using feature vectors | Data science interview
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- What would a dataset to train models to detect bots look like? How would you approach collecting this data? | Data science interview
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- Technical implementation details python libraries, cloud services, etc | Data science interview
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- Any questions for me? | Data science interview
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- Post-interview breakdown & analysis
Description:
Experience a comprehensive mock data science interview in this 1 hour 28 minute video featuring Kylie Ying. Dive into a real-world task of developing a model to identify bots on a social media platform. Learn about feature vectorization, one-hot encodings, and dataset building. Follow along as the interview covers behavioral questions, task overview, feature investigation, classification model implementation, dataset creation, technical details, and a post-interview analysis. Gain valuable insights into the data science interview process and enhance your skills in tackling complex machine learning problems.

Full Data Science Mock Interview Featuring Kylie Ying

Keith Galli
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