What features would you use to predict the Uber ETA for ride requests?Data processingFeature SelectionModel SelectionCross ValidationEvaluation MetricsTesting...
How would you evaluate the predictions of an Uber ETA model?
How would you evaluate the predictions of an Uber ETA model?Data processingFeature SelectionModel SelectionCross ValidationEvaluation MetricsTesting and...
Describe how you would build a model to predict Uber ETAs after a rider requests a ride.
Describe how you would build a model to predict Uber ETAs after a rider requests a ride.Data processingFeature SelectionModel SelectionCross ValidationEvaluation...
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?
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...
Precision vs Accuracy Vs Recall?
Precision vs Accuracy Vs Recall?Accuracy - Accuracy is the most intuitive performance measure and it is simply a ratio of correctly predicted observation...
Error vs variance vs bias?
Error vs variance vs bias?In statistics and machine learning, the bias-variance tradeoff is the property of a set of predictive models whereby models...
False negatives vs false positives? When is either one worse than the other?
False negatives vs false positives? When is either one worse than the other?False positive: A false positive error, or in short a false positive, commonly...
Describe your data science process start to finish?
Describe your data science process start to finish?ID: Identify question, identify best data, identify metrics or features. LOAD: separate training and...
Data science vs machine learning vs AI?
Data science vs machine learning vs AI?Data Science: Data science is the extraction of relevant insights from data. It uses various techniques from many...
How would you find correlation between a categorical variable and a continuous variable?
How would you find correlation between a categorical variable and a continuous variable?Distance Metrics: Although the concept of "distance" is often...
How do you treat null/missing values? Name 3 methodologies.
How do you treat null/missing values? Name 3 methodologies.Last Observation Carried Forward (LOCF) & Next Observation Carried Backward (NOCB)This...
How can outlier values be treated?
How can outlier values be treated?Univariate outliers: Box plots, histograms, distributionsMultivariate method: Fit several miltivariate models and view...
What is data normalization? Name 2 normalization methodologies.
What is data normalization? Name 2 normalization methodologies.In databases it is makin sure there is no redundancy and data dependencies are all logical....
What is the role/importance of data cleaning?
What is the role/importance of data cleaning?Unstrucutred data is totally unusable until cleaned. Data coming from differnet soruces can't be compared...
What are success metrics vs tracking metrics?
What are success metrics vs tracking metrics?Metrics: What you measure to gauge performance or progress within a company or organization. Your most important...
What kind of metric would you make to measure success of a program (marketing) and how do you define them?
What kind of metric would you make to measure success of a program (marketing) and how do you define them?Measure by categeory, segment metrics based...
Let's say an app was getting a redesign. How do you know if the redesign was successful?
Let's say an app was getting a redesign. How do you know if the redesign was successful?Average page time (without force quit)Average session duration...
We noticed a steep decline in users in a certain area of the world, how would you address/asses?
We noticed a steep decline in users in a certain area of the world, how would you address/asses?Active users (ADAU, MAU) - ADAU = total number of active...
Define precision and recall.
Define precision and recall.Answer: Recall is also known as the true positive rate: the amount of positives your model claims compared to the actual number...
Auto Encoder vs Encoder Decoder
Auto Encoder vs Encoder DecoderAutoencoders exhibit encoder-decoder structure:Autoencoders are used in supervised as well as unsupervised learning...
What operates better, LMS or Perceptron?
What operates better, LMS or Perceptron?LMS; perceptron converges to a solution to correctly categorize patterns, but its result is prone to noise since...
How do you use the Taylor Series against the performance index?
How do you use the Taylor Series against the performance index?By approximating the p.i., we are limiting the expansion finitely because its derivatives...
In a single-neuron perceptron, what weights and biases are changed to distinguish between 2 outputs?
In a single-neuron perceptron, what weights and biases are changed to distinguish between 2 outputs?The weights in the weight matrix that differentiate...
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