Prepare for and practice interview questions from Assa Abloy Group.

Assa Abloy Group Interview Questions

Assa Abloy Group Interview Guides

Data Structures & Algorithms

Given two sorted lists, write a function to merge them into one sorted list.

Merge Sorted Lists

Find the missing integer from a array of consequtive integers

Find the Missing Number

Write a function n_frequent_words that returns the top N frequent words and their frequencies, and state its run-time

Get Top N Frequent Words

Reconstruct the path of a trip so that the trip tickets are in order.

Scrambled Tickets

Write a function one_element_removed that returns the integer removed from list Y in O(1) space and O(n) time without using set

One Element Removed

Machine Learning

How do we deal with the missing square footage data to construct our model

Missing Housing Data

Why can the same machine learning algorithm produce different success rates on the same dataset

Same Algorithm Different Success

What are some reasons why measuring bias would be important in building this particular model

Food Delivery Times

How would you evaluate whether a decision tree is the right model and assess its performance before and after deployment

Decision Tree Evaluation

How does random forest generate the forest and why use it over logistic regression

Random Forest Explanation

Product Sense & Metrics

How would you determine the cause and what would you do with these users

Inactive Users

The role of A/B testing in measuring the success rate of an analytics experiment

Success Measurement

Vision Setting and Execution Strategy

How would you approach sizing the market, segmenting users, identifying competitors, and building a marketing plan for a new smart fitness tracker?

Smart Fitness Tracker Launch

Design the autocomplete and explain how you would measure its effectiveness

Facebook Autocomplete

Statistics

What are the assumptions of linear regression?

Assumptions of Linear Regression

What is the downside of only using the R-Squared (R^2) value to determine a relationship between two variables

Using R Squared

Explain the difference between covariance and correlation and provide an example

Covariance vs Correlation

How do you detect and handle correlation between variables in linear regression, and what happens if you ignore it

Correlation in Regression

What does it mean to "bootstrap" a data set?

Bootstrapping Samples

Behavioral

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

Describing a data project and its challenges

Hurdles In Data Projects

How would you negotiate and resolve disagreements when a client rejects your proposed solution?

Client Solution Pushback

What do you tell an interviewer when they ask you what your strengths and weaknesses are?

Your Strengths and Weaknesses

Given two sorted lists, write a function to merge them into one sorted list.

Bonus: What’s the time complexity?

Example:

Input:

<pre tabindex="0" class="chroma"><code>list1 = [1,2,5]
list2 = [2,4,6]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def merge_list(list1,list2) -&gt; [1,2,2,4,5,6]
</code></pre>

You have two sorted lists, one with m elements and one with n elements. What would be the time complexity of merging the two lists via merge sort?

You have two sorted lists, one with m elements and one with n elements. What would be the time complexity of merging the two lists via merge sort? 

Merging Lists Complexity

You have an array of integers, <code>nums</code> of length <code>n</code> spanning <code>0</code> to <code>n</code> with one missing. Write a function <code>missing_number</code> that returns the missing number in the array.

Note: Complexity of $O(n)$ required.

Example:

Input:

<pre tabindex="0" class="chroma"><code>nums = [0,1,2,4,5] 
missing_number(nums) -&gt; 3
</code></pre>

Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle it?

Consider a trip from one city to another that may contain many layovers. Given the list of flights out of order, each with a starting city and end city, write a function <code>plan_trip</code> to reconstruct the path of the trip so the trip tickets are in order.

Example:

For a trip from Bombay to Beijing:

Input:

<pre tabindex="0" class="chroma"><code>flights = [
 [&#39;Chennai&#39;, &#39;Bangalore&#39;], 
 [&#39;Bombay&#39;, &#39;Delhi&#39;], 
 [&#39;Goa&#39;, &#39;Chennai&#39;], 
 [&#39;Delhi&#39;, &#39;Goa&#39;], 
 [&#39;Bangalore&#39;, &#39;Beijing&#39;]
]
output = [
 [&#39;Bombay&#39;, &#39;Delhi&#39;], 
 [&#39;Delhi&#39;, &#39;Goa&#39;], 
 [&#39;Goa&#39;, &#39;Chennai&#39;], 
 [&#39;Chennai&#39;, &#39;Bangalore&#39;], 
 [&#39;Bangalore&#39;, &#39;Beijing&#39;],
]
</code></pre>

Write a Python function called <code>max_profit</code> that takes a list of integers, where the i-th integer represents the price of a given stock on day i, and returns the maximum profit you can achieve by buying and selling the stock.

You may complete, at most, two complete buy/sell transactions to maximize profits on a stock.

Input:

<pre tabindex="0" class="chroma"><code>prices = [3, 3, 5, 0, 0, 3, 1, 4]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def max_profit(prices) -&gt; 6
</code></pre>

Explanation:

<pre><code>Buy on day 4 (price = 0) and sell on day 6 (price = 3): profit = 3 - 0 = 3.
Then buy again on day 7 (price = 1) and sell on day 8 (price = 4): profit = 4 - 1 = 3.
Total profit: 3 + 3 = 6.
</code></pre>

Find the maximum profit from at most two stock buy/sell transactions

Maximum Profit

There are two lists, <code>list X</code> and <code>list Y</code>. Both lists contain integers from <code>-1000</code> to <code>1000</code> and are identical to each other except that one integer is removed in <code>list Y</code> that exists in <code>list X</code>.

Write a function <code>one_element_removed</code> that takes in both lists and returns the integer that was removed in $O(1)$ space and $O(n)$ time without using the python set function.

Example:

Input:

<pre tabindex="0" class="chroma"><code>list_x = [1,2,3,4,5]
list_y = [1,2,4,5]

one_element_removed(list_x, list_y) -&gt; 3
</code></pre>

Which of the following methods would be the most efficient way of identifying what element is not included in two lists of integers that differ by a single element being removed?

For example, if the lists are <code>[1,2,3,4,5]</code> and <code>[1,2,4,5]</code>, the function should return <code>3</code>

Which of the following methods would be the most efficient way of identifying what element is not included in two lists of integers that differ by a single element being removed? 

For example, if the lists are `[1,2,3,4,5]` and `[1,2,4,5]`, the function should return `3`

Efficiently Identifying Missing Integer

<ol>
<li>Given an example paragraph string and an integer <code>N</code>, write a function <code>n_frequent_words</code> that returns the top <code>N</code> frequent words in the posting and the frequencies for each word.</li>

<li>What’s the function run-time?</li>
</ol>

Example:

Input:

<pre tabindex="0" class="chroma"><code>posting = &#34;&#34;&#34;
Herbal sauna uses the healing properties of herbs in combination with distilled water. 
The water evaporates and distributes the effect of the herbs throughout the room. 
A visit to the herbal sauna can cause real miracles, especially for colds. 
&#34;&#34;&#34; 
n = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>n_frequent_words(posting,N) = [
 (&#39;the&#39;, 6), 
 (&#39;herbal&#39;, 2), 
 (&#39;sauna&#39;, 2),
]
</code></pre>

You’re given a string that may contain the characters <code>{</code>, <code>}</code>, <code>[</code>, <code>]</code>, <code>(</code>, and <code>)</code>.

Task: Verify that the string is balanced. A balanced string is one where every opening character, <code>{</code>, <code>[</code>, or <code>(</code>, has a corresponding closing character, <code>}</code>, <code>]</code>, or <code>)</code>.

Write a function called <code>is_balanced(string: str) -&gt; bool</code> which verifies the balance of a string.

Example:

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;(())[]{}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{([(){}])()}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{}[]())&#39;) -&gt; False
</code></pre>

<hr/>

Write a function that tests whether a string of brackets is balanced.

The Brackets Problem

Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics.

Return the ordered pair (precision, recall).

Example:

Input:

<pre tabindex="0" class="chroma"><code>
P = [[121, 9],
 [17, 144]]
</code></pre>

where P represents the following table

<table>
<thead>
<tr>
<th></th>
<th>Predicted =TRUE</th>
<th>Predicted =FALSE</th>
</tr>
</thead>

<tbody>
<tr>
<td>Actual =TRUE</td>
<td>121</td>
<td>9</td>
</tr>

<tr>
<td>Actual =FALSE</td>
<td>17</td>
<td>144</td>
</tr>
</tbody>
</table>
Output:

<pre tabindex="0" class="chroma"><code>def precision_recall(P) -&gt; (0.931, 0.877,)
</code></pre>

Write a function to calculate precision and recall metrics.

Precision and Recall

Given a 2D terrain represented by an array of non-negative integers, where each integer represents the height of a terrain level at that index, implement an algorithm to calculate the total amount of rainwater that can be trapped in this terrain.
Consider that rainwater can only be trapped between two terrain levels with higher heights, and the trapped water cannot flow out through the edges.

The algorithm should have an optimal time complexity of O(n) and a space complexity of O(n).
 Provide a detailed explanation of the algorithm and its implementation in Python.

Example:

<table>
<thead>
<tr>
<th>Index</th>
<th>0</th>
<th>1</th>
<th>2</th>
<th>3</th>
<th>4</th>
</tr>
</thead>

<tbody>
<tr>
<td>Terrain Level</td>
<td>3</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>4</td>
</tr>

<tr>
<td>Trapped Water</td>
<td>0</td>
<td>3</td>
<td>1</td>
<td>3</td>
<td>0</td>
</tr>
</tbody>
</table>
In this table, the ‘Index’ row represents the position of the terrain levels, the ‘Terrain Level’ row shows the height of the terrain at each index, and the ‘Trapped Water’ row illustrates the trapped rainwater between the terrain levels. The total trapped rainwater in this example is 7 units (3 + 1 + 3).

Input:

<pre tabindex="0" class="chroma"><code>terrainLevels = [3, 0, 2, 0, 4]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>7
</code></pre>

In this example, the terrain is represented by the <code>terrainLevels</code> array. The algorithm should calculate the total trapped rainwater, which is 7 units in this case. The trapped rainwater is formed between the heights of 3, 0, 2, 0, and 4.

Given a 2D terrain array, calculate the total amount of trapped rainwater with O(n) time and O(n) space

Level Of Rain Water In 2D Terrain

Say you are tasked with analyzing how well a model fits the data given. You want to determine a relationship between two variables.

What is the downside of only using the R-Squared $(R^2)$ value to do so?

In the context of regression analysis, why is it misleading to rely solely on a high R-squared ($R^2$) value to infer a causal relationship between variables?

In the context of regression analysis, why is it misleading to rely solely on a high R-squared ($R^2$) value to infer a causal relationship between variables?

Using R Squared I

Which of the following best describes the R-squared ($R^2$) value in the context of a regression model?

Which of the following best describes the R-squared ($R^2$) value in the context of a regression model?

Using R Squared II

What is a limitation of using R-squared ($R^2$) as the only metric to evaluate a regression model's fit?

What is a limitation of using R-squared ($R^2$) as the only metric to evaluate a regression model's fit?

Using R Squared III

What is the difference between covariance and correlation? Provide an example.

How does random forest generate the forest? Additionally, why would we use it over other algorithms such as logistic regression?

What happens when you average the output on multiple decision trees?

What happens when you average the output on multiple decision trees?

Average Trees

Let’s say we want to improve the matching algorithm for drivers and riders for Uber. The engineering team has added a new column to the <code>drivers</code> table called <code>weighting</code>. It contains a weighted value, which they hope will lead to better matching.

Given this table of drivers, write a query to perform a weighted random selection of a driver based on the driver weight.

Example:

Input:

<code>drivers</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>weighting</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Select a (weight) random driver from the database.

Random Weighted Driver

Given a <code>ListNode</code> representing the head of a linked list, write a function <code>is_cyclic</code> which returns <code>True</code> if a linked list is cyclic and <code>False</code> if it is not. A linked list is cyclic when there is no tail to the linked list, and the supposed tail is attached to another node inside the list itself, creating a cycle.

A <code>ListNode</code> is defined as:

<pre tabindex="0" class="chroma"><code>class ListNode:
	value: ListNode = None
 next: ListNode = None
</code></pre>

Example:

Input:

<img src="/s3/questions/1a65651d-a483-4481-b073-2738d65ab9d7.png" alt="image"/>

Output:

<pre tabindex="0" class="chroma"><code>def is_cyclic(head) -&gt; True
</code></pre>

Cyclic Detection

Three zebras are chilling in the desert. Suddenly a lion attacks.
Each zebra is sitting on a corner of a triangle with sides of equal length.
Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length. Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length.  Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?



Three Zebras

Brainteasers

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years but found that around 20% of the listings are missing square footage data.

How do we deal with the missing data to construct our model?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?



Why would the same machine learning algorithm generate different success rates using the same dataset?

Note: When they ask us an ambiguous question, we need to gather context and restate it in a way that’s clear for us to answer.

An electronics retail company tracks its sales and wants to run a performance analysis. They’re hoping to categorize sales into different groups, based on the amount of sales and the region where the sale occurred. The conditions for categorization are:

<ul>
<li>Standard Sales: Any sales below 2000 are considered standard, except if they occur in the <code>East</code> region, or in the month of July.</li>
<li>Premium Sales: Any sales that are over or equal to 2000, or any sales in the <code>East</code> region (regardless of the amount), are considered premium, except again during the month of July.</li>
<li>Promotional Sales: All sales made in the promotional period of July, regardless of the amount or region, are considered promotional.</li>
</ul>

The company wants a report that sums these amounts by region to help with financial planning and bonus allocations.

Note: You may assume that table contains data only for 2023

Example:

Input:

<code>sales</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>sale_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>employee_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>product_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>sale_amount</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>sale_date</code></td>
<td>DATE</td>
</tr>

<tr>
<td><code>region</code></td>
<td>TEXT</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>region</code></td>
<td>TEXT</td>
</tr>

<tr>
<td><code>total_sales</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>premium_sales</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>standard_sales</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>promotional_sales</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>

Categorize sales based on the amount of sales and the region

Categorize Sales

Given two strings, write a function to return <code>True</code> if the strings are anagrams of each other and <code>False</code> if they are not.

Note: A word is not an anagram of itself.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>string_1 = &#34;listen&#34;
string_2 = &#34;silent&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>True
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>string_1 = &#34;banana&#34;
string_2 = &#34;bandana&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>False
</code></pre>

Write a function to return True if two strings are anagrams of each other and False if they are not

Valid Anagram

Given a list, write a function <code>encode</code> which one-hot encodes the items in the list. When one-hot encoding, the most significant bit (index zero) should be represented by the first unique element in the list.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>elements = [1, 3, 4, 3, 2, 1]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def encode(elements) -&gt; [[1, 0, 0, 0], [0, 1, 0, 0],
 [0, 0, 1, 0], [0, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0]]
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>elements = [&#39;hi&#39;, &#39;hello&#39;, &#39;amazing&#39;, &#39;amazing&#39;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def encode(elements) -&gt; [[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 0, 1]]
</code></pre>

Implement one-hot encoding algorithmically.

One-Hot Encoder

Explain the difference between the XGBoost and random forest algorithms and give an example where you would use one over the other.

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

XGBoost vs Random Forest: Choice

Explain the difference between XGBoost and random forest and give an example where you would use one over the other

Xgboost vs Random Forest

Write a function to determine the mode of an array of integers.

The list may have one mode, more than one mode, or no mode at all. If the list has multiple modes, return them in ascending order.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 2, 2, 3, 4]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>mode(nums) -&gt; [2]
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1,1,2,2]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>mode(nums) -&gt; [1, 2]
</code></pre>

This question is about finding the mode of a given array. The mode is the value that appears most frequently in a data set. If there are multiple modes, return them in ascending order.

Finding The Mode

Let’s say that you work as a data scientist at a food delivery company.

You are tasked with building a model to predict food preparation times at a restaurant from the time when a customer sends in the order to when the meal is ready for the driver to pick up.

What are some reasons why measuring bias would be important in building this particular model?

What are the assumptions of linear regression?

Which assumption of the residuals of the standard linear regression model can not be overcome by increasing the sample size?

Regression assumptions

Implement Dijkstra’s shortest path algorithm for a given graph with a known source node.

A graph format is a dictionary of nodes as key and the value is a dictionary of neighbors to that node with the distance between them as follow.

Note: set the previous node of the source node to <code>None</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>
source_node = &#39;A&#39;

graph = {
 &#39;A&#39;: {
 &#39;D&#39;: 1,
 &#39;B&#39;: 6
 },
 &#39;B&#39;: {
 &#39;A&#39;: 6,
 &#39;D&#39;: 2,
 &#39;E&#39;: 2,
 &#39;C&#39;: 5
 },
 &#39;C&#39;: {
 &#39;B&#39;: 5,
 &#39;E&#39;: 5
 },
 &#39;D&#39;: {
 &#39;A&#39;: 1,
 &#39;B&#39;: 2,
 &#39;E&#39;: 1
 },
 &#39;E&#39;: {
 &#39;C&#39;: 5,
 &#39;B&#39;: 2
 }

 }


</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>
output_table = {
 &#39;A&#39;: {
 &#39;ShortestDistance&#39;: 0,
 &#39;PreviousVertex&#39;: None
 },
 &#39;B&#39;: {
 &#39;ShortestDistance&#39;: 3,
 &#39;PreviousVertex&#39;: &#39;D&#39;
 },
 &#39;C&#39;: {
 &#39;ShortestDistance&#39;: 7,
 &#39;PreviousVertex&#39;: &#39;E&#39;
 },
 &#39;D&#39;: {
 &#39;ShortestDistance&#39;: 1,
 &#39;PreviousVertex&#39;: &#39;A&#39;
 },
 &#39;E&#39;: {
 &#39;ShortestDistance&#39;: 2,
 &#39;PreviousVertex&#39;: &#39;D&#39;
 }
 }
</code></pre>

<img src="/s3/questions/785715d4-3305-4b9f-bdd7-33d5cf987bdb.png" alt="image"/>

Implement Dijkstra's shortest path algorithm for a given graph with a known source node.

Dijkstra implementation

You are given two lists: a full list and a missing list. The full list contains a list of integers, while the missing list contains all the integers from the full list except for one. Your task is to create a function that finds the missing element.

For example:

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>full = [1, 2, 3, 4, 5]
missing = [1, 2, 3, 5]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>one_element_removed(full, missing) -&gt; 4
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>full = [4,-6,3,10,11,150,120]
missing = [4,-6,3,10,11,150]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>one_element_removed(full, missing) -&gt; 120
</code></pre>

Example 3:

Input:

<pre tabindex="0" class="chroma"><code>full = [17, 11, 15, 19, 21, 11]
missing = [17, 15, 19, 21, 11]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>one_element_removed(full, missing) -&gt; 11
</code></pre>

In this case, one of the 11’s is missing from the missing list. Your function should return the repeated number.

This question tests your ability to manipulate lists and use bitwise operations to solve a problem. You are given two lists, one with all integers and the other missing one integer from the full list. Your task is to create a function to find the missing integer.

Find the Missing Element

You’re a data scientist at YouTube. Leadership wants to revisit how the platform measures success, not for a specific new feature, but for the product as a whole given its current state.

How would you define and measure success for YouTube? Identify your primary and secondary metrics, explain your rationale for each, and discuss how you would choose the right thresholds for any engagement-based metrics you propose.

You’ve been tasked with building a classification machine-learning model to predict whether a transaction is either fraud or not fraud for a credit card company. You have ten years of historical data on transactions, including a flag for whether a transaction was manually identified as fraud.

Describe how you might go about building a fraud detection model for credit card transactions. Be sure to mention the possible model types, discuss the bias-variance tradeoff in model development, and address any complexities that arise from the class imbalance.

Input features in the data include:

<ul>
<li>Transaction amount</li>
<li>Merchant category for the transaction</li>
<li>Zip code for the merchant</li>
<li>Zip code for the billing address</li>
<li>Average transaction amount for the account over the past six months</li>
</ul>

Output feature:

<ul>
<li>0/1 flag for fraud (0 = not fraud, 1 = fraud)</li>
</ul>

Note: Fraudulent transactions are (thankfully) a very small percentage of all historical transactions. Assume fraudulent transactions are 0.01% of historical data.While building the model to perform the classification, you need to consider the bias/variance tradeoff, and take into account the fact that there is a class imbalance (very few of the observations are “fraud”).

Bias variance tradeoff and class imbalance in finance

Bias - Variance Tradeoff and Class Imbalance in Finance

You work as a data engineer in X (formerly Twitter), in a team responsible for building the platform’s trending chart for monitoring global social media trends. The system ingests a high-volume stream of tweets, and your team needs to partition incoming tweets into buckets based on hashtags as they arrive.

How would you architect the data pipeline and select data structures to efficiently partition and store tweets by hashtag in real time?

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