Suppose you're working as a data scientist at Facebook. How would you measure the success of private stories on Instagram, where only certain chosen friends can see the story?
Data processing
Feature Selection
Model Selection
Cross Validation
Evaluation Metrics
Testing and Roll Out
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Data Science
- What features would you use to predict the Uber ETA for ride requests?
- How would you evaluate the predictions of an Uber ETA model?
- Describe how you would build a model to predict Uber ETAs after a rider requests a ride.
- Precision vs Accuracy Vs Recall?
- Error vs variance vs bias?
- False negatives vs false positives? When is either one worse than the other?
- Describe your data science process start to finish?
- Data science vs machine learning vs AI?
- How would you find correlation between a categorical variable and a continuous variable?
- How do you treat null/missing values? Name 3 methodologies.
- How can outlier values be treated?
- What is data normalization? Name 2 normalization methodologies.
- What is the role/importance of data cleaning?
- What are success metrics vs tracking metrics?
- What kind of metric would you make to measure success of a program (marketing) and how do you define them?
- Let's say an app was getting a redesign. How do you know if the redesign was successful?
- We noticed a steep decline in users in a certain area of the world, how would you address/asses?
- What are the two methods used for the calibration in Supervised Learning?
- Which method is frequently used to prevent overfitting?
- What is the difference between heuristic for rule learning and heuristics for decision trees?
- What is Perceptron in Machine Learning?
- Explain the two components of Bayesian logic program?
- What are Bayesian Networks (BN) ?
- Why instance based learning algorithm sometimes referred as Lazy learning algorithm?