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Machine Learning

1000 Sample Classifier

Creating a machine learning model for evaluating a patient's health

Risk Assessment Model

Building a model to predict if a driver on Uber will accept a ride request or not

Ride Requests Model

Product Sense & Metrics

Promoting Instagram

You work as a data scientist for ride-sharing company.  An executive asks how you would evaluate whether a 50% rider discount promotion is a good or bad idea?  How would you implement it? What metrics would you track?

Rider Discount

Statistics

P-value to a Layman

What are confidence intervals and how are they useful

Confidence Interval Explanation

Brainteasers

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

Analytics

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

When an interviewer asks you a question along the lines of:

<ul>
<li>Why did you apply to our company?</li>
<li>What are you looking for in your next job?</li>
<li>What makes you a good fit for our company?</li>
</ul>

How should you respond?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

Why Do You Want to Work With Us I

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

Why Do You Want to Work With Us II

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

Why Do You Want to Work With Us III

How would you explain what a p-value is to someone who is not technical?

What does a p-value in a statistical test represent?

What does a p-value in a statistical test represent?

P-value to a Layman I

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?

What is a confidence interval for a statistic? Why is it useful to know the confidence interval for a statistic and how do you calculate it?

You work as a machine learning engineer for a health insurance company. Design a machine learning model, which given a set of health features, classifies if the individual will undergo major health issues or not.

Let’s say you work on the growth team at Facebook and are tasked with promoting Instagram from within the Facebook app.

Where and how could you promote Instagram through Facebook?

You're promoting Instagram within the Facebook app. Which of the following methods involves leveraging network effects?

You're promoting Instagram within the Facebook app. Which of the following methods involves leveraging network effects?

Promoting Instagram I

To promote Instagram on Facebook, you consider allowing Instagram users to post pictures to Facebook. How could you measure the success of this feature?

To promote Instagram on Facebook, you consider allowing Instagram users to post pictures to Facebook. How could you measure the success of this feature?

Promoting Instagram II

In a strategy to promote Instagram from within Facebook, what concept might you employ to improve the value of the service?

In a strategy to promote Instagram from within Facebook, what concept might you employ to improve the value of the service?

Promoting Instagram III

You are building a binary classifier on a dataset with 1000 samples and 10,000 features.

Would you use logistic regression? Why or why not?

You’re tasked with building a model to predict if a driver on Uber will accept a ride request or not. 

<ol>
<li>What algorithm would you use to build this model? What are the tradeoffs between different classifiers?</li>

<li>What features would you use?</li>
</ol>

You work as a data scientist for ride-sharing company.

An executive asks how you would evaluate whether a 50% rider discount promotion is a good or bad idea?

How would you implement it? What metrics would you track?

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

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