- Where did you get your dataset? How large is it?
- Was cleaning the data time consuming? Can you explain why?
- Why was your error rate so low when you used this algorithm?
- Did you do any cross validation?
- What portion of the dataset was for training and what part was for testing accuracy?
- Why was one algorithm faster than another?
- How many items were in your sample data stream?
- Why did one algorithm use more memory than another?
- Can you show a graph for the memory usage to data size ratio?
- Why didn't you use any deterministic algorithms?
- Did you measure the discounted cumulative gain (DCG)?
- Can you explain the idea behind the formulas for location filtering and activity filtering?
- What factors affect accuracy?
- What benefit does machine learning provide for your users?
- What benefit does collaborative filtering provide?
- How do you generate recommendations?
- How do you know what users want?
- How did you transfer PLACELAB into Java?
- What do the X and Y axes represent?
- If new data keeps coming in, how can you incorporate it?
- What differences would you expect if you used a different dataset?
- Would the technical part change with a different type of dataset?
- How do you use GPS?
- Can you explain more about JSON?
- What's unique about JSON?
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