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Cirrus logic Interview Questions

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Data Structures & Algorithms

Find the missing integer from a array of consequtive integers

Find the Missing Number

Given a list of integers, find the index at which the sum of the left half of the list is equal to the right half.

Equivalent Index

Given an integer N, write a function that returns all of the prime numbers up to N

Prime to N

Write a function `stopwords_stripped` that removes stop words from a string and lowercases it

Stop Words Filter

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

Random Forest Explanation

When should you use regularization versus cross-validation

Regularization and Validation

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Paired Products

Write a query to get the number of customers that were upsold

Upsell Transactions

Create a report displaying which shipments were delivered to customers during their membership period.

Completed Shipments

Daily Active Users

Behavioral

Describing a data project and its challenges

Hurdles In Data Projects

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

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

Your Strengths and Weaknesses

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

Why Do You Want to Work With Us

AI & Agentic Systems

How would you build and justify the components of a Transformer encoder layer in PyTorch for large-scale text data?

Transformer Encoder Layer

Design a system for a voice assistant to distinguish questions from statements in a language where both share the same word order.

Question Detection Ambiguity

Design a RAG system that restricts LLM responses exclusively to ingested data, preventing use of pre-trained knowledge.

RAG Strict Source Control

Let’s say you are part of the Gmail team at Google.

Your manager asks your team to develop a classifier to tag emails as spam or not spam.

One of your colleagues suggests using a Naive Bayes classifier. But another colleague disagrees because Naive Bayes is a generative model, and they say it would be better to use a discriminative model like Logistic Regression.

How would you explain to your manager the difference between a generative and discriminative model? And which one of your co-workers is correct?

Explain the difference between a generative and discriminative model and which coworker is correct

Generative vs Discriminative

Write a SQL query to select the 2nd highest salary in the engineering department.

Note: If more than one person shares the highest salary, the query should select the next highest salary.

Example:

Input:

<code>employees</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>first_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>last_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>department_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>departments</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>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

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

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

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>

We’re given a table of product purchases. Each row in the table represents an individual user product purchase.

Write a query to get the number of customers that were upsold, or in other words, the number of users who bought additional products after their first purchase.

Note: If the customer purchased two things on the same day, that does not count as an upsell, as they were purchased within a similar timeframe.

Example:

Input:

<code>transactions</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>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

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

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

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

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

Let’s say we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.

Write a query to randomly sample a row from this table.

Input:

<code>big_table</code> table

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

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

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to randomly sample a row from a big table.

Random SQL Sample

Let’s say we have two tables, <code>transactions</code> and <code>products</code>. Hypothetically the <code>transactions</code> table consists of over a billion rows of purchases bought by users.

We are trying to find paired products that are often purchased together by the same user, such as wine and bottle openers, chips and beer, etc..

Write a query to find the top five paired products and their names.

Notes:
 For the purposes of satisfying the test case, p2 should be the item that comes first in the alphabet.
 The <code>qty</code> column represents paired products count

Example:

Input:

<code>transactions</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>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

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

<tr>
<td><code>quantity</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>products</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>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>price</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
Output:

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

<tbody>
<tr>
<td><code>p1</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>p2</code></td>
<td>VARCHAR</td>
</tr>

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

Given an integer <code>N</code>, write a function that returns a list of all of the prime numbers up to <code>N</code>.

Note: Return an empty list there are no prime numbers less than or equal to <code>N</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>N = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def prime_numbers(N) -&gt; [2,3]
</code></pre>

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

To finish a class, students must pass four exams (exam ids: 1,2,3 and 4).

Given a table <code>exam_scores</code> containing the data about all of the exams that students took, form a new table to track the scores for each student.

Note: Students took each exam only once.

Example:

For the given input:

<table>
<thead>
<tr>
<th><code>student_id</code></th>
<th><code>student_name</code></th>
<th><code>exam_id</code></th>
<th><code>score</code></th>
</tr>
</thead>

<tbody>
<tr>
<td>100</td>
<td><code>Anna</code></td>
<td>1</td>
<td>71</td>
</tr>

<tr>
<td>100</td>
<td><code>Anna</code></td>
<td>2</td>
<td>72</td>
</tr>

<tr>
<td>100</td>
<td><code>Anna</code></td>
<td>3</td>
<td>73</td>
</tr>

<tr>
<td>100</td>
<td><code>Anna</code></td>
<td>4</td>
<td>74</td>
</tr>

<tr>
<td>101</td>
<td><code>Brian</code></td>
<td>1</td>
<td>65</td>
</tr>
</tbody>
</table>
the expected output should be:

<table>
<thead>
<tr>
<th><code>student_name</code></th>
<th><code>exam_1</code></th>
<th><code>exam_2</code></th>
<th><code>exam_3</code></th>
<th><code>exam_4</code></th>
</tr>
</thead>

<tbody>
<tr>
<td><code>Anna</code></td>
<td>71</td>
<td>72</td>
<td>73</td>
<td>74</td>
</tr>

<tr>
<td><code>Brian</code></td>
<td>65</td>
<td>NULL</td>
<td>NULL</td>
<td>NULL</td>
</tr>
</tbody>
</table>
Input:

<code>exam_scores</code> table

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

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

<tr>
<td><code>student_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>exam_id</code></td>
<td>INTEGER</td>
</tr>

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

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

<tbody>
<tr>
<td><code>student_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>exam_1</code></td>
<td>INT</td>
</tr>

<tr>
<td><code>exam_2</code></td>
<td>INT</td>
</tr>

<tr>
<td><code>exam_3</code></td>
<td>INT</td>
</tr>

<tr>
<td><code>exam_4</code></td>
<td>INT</td>
</tr>
</tbody>
</table>

List out the exams sources of each student in MySQL

Exam Scores

As an accountant for a local grocery store, you have been tasked with calculating the daily sales of each product since their last restocking.

You have been provided with three tables: <code>products</code>, <code>sales</code>, and <code>restocking</code>. The <code>products</code> table contains information about each product, the <code>sales</code> table records the sales transactions, and the <code>restocking</code> table tracks the restocking events.

Write a query to retrieve the running total of sales for each product since its last restocking event.

Notes: The <code>sales_since_last_restock</code> column represents the cumulative sales of the product for each day since its last restocking event. Order the result set by <code>product_id</code>.

Example:

Input:

Table <code>products</code>:

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

<tbody>
<tr>
<td>product_id</td>
<td>int</td>
</tr>

<tr>
<td>product_name</td>
<td>varchar</td>
</tr>
</tbody>
</table>
Table <code>sales</code>:

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

<tbody>
<tr>
<td>sales_id</td>
<td>int</td>
</tr>

<tr>
<td>product_id</td>
<td>int</td>
</tr>

<tr>
<td>date</td>
<td>date</td>
</tr>

<tr>
<td>sold_count</td>
<td>int</td>
</tr>
</tbody>
</table>
Table <code>restocking</code>:

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

<tbody>
<tr>
<td>restock_id</td>
<td>int</td>
</tr>

<tr>
<td>product_id</td>
<td>int</td>
</tr>

<tr>
<td>restock_date</td>
<td>date</td>
</tr>
</tbody>
</table>
Output

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

<tbody>
<tr>
<td>product_name</td>
<td>varchar</td>
</tr>

<tr>
<td>date</td>
<td>date</td>
</tr>

<tr>
<td>sales_since_last_restock</td>
<td>int</td>
</tr>
</tbody>
</table>

Calculate daily sales of each product since last restocking.

Cumulative Sales Since Last Restocking

Say you are tasked with designing a data mart or data warehouse for a new online retailer.

How would you design the system?

Note: Sketch a star schema to explain your design.

Design a data warehouse for a new online retailer

Retailer Data Warehouse

Data Modeling

Given a list of integers, find the index at which the sum of the left half of the list is equal to the right half.

If there is no index where this condition is satisfied return -1.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 7, 3, 5, 6]
</code></pre>

Output:

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

Example 2:

Input:

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

Output:

<pre tabindex="0" class="chroma"><code>equivalent_index(nums) -&gt; -1
</code></pre>

Let’s say that you’re a data scientist working on a distribution team at Amazon.

Create a report displaying which shipments were delivered to customers during their membership period.

If the transaction is shipped during the membership period, column <code>is_member</code> should have the value <code>Y</code>. If not, the column should have the value <code>N</code>.

Hint: You may assume that <code>customer_id</code> is unique and that shipments are made only to registered customers.

Example:

Input:

<code>customers</code> table

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

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

<tr>
<td><code>membership_start_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>membership_end_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<code>shipments</code> table

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

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

<tr>
<td><code>ship_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>customer_id</code></td>
<td>INTEGER</td>
</tr>

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

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

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

<tr>
<td><code>ship_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>customer_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>is_member</code></td>
<td>TEXT</td>
</tr>

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

Let’s say your manager is running A/B tests on a website. You find out that your manager has run an A/B test with 20 different variants and come back to you that one of the variants is significant.

Would you think there was anything fishy about the results?

Your manager reconfigured an A/B test from 2 to 20 different variants, while keeping all other parameters unchanged. They come back to you that one of the variants is significant.

Is this conclusion likely to be correct? Why or why not?

Your manager reconfigured an A/B test from 2 to 20 different variants, while keeping all other parameters unchanged. They come back to you that one of the variants is significant.

Is this conclusion likely to be correct? Why or why not?

Twenty Variant Test

Would you think there was anything fishy about an A/B test run with 20 different variants where one is significant

Twenty Variants

A/B Testing

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

Let’s say we have a sample size of $n$. The margin of error for our sample size is 3.

How many more samples would we need to decrease the margin of error to 0.3?

Let's say we have a sample size of N. The margin of error for our sample size is 3.

How many more samples would we need to decrease the margin of error to 0.3?

Let's say we have a sample size of N. The margin of error for our sample size is 3.

How many more samples would we need to decrease the margin of error to 0.3?

Reducing Error Margin

How many more samples are needed to decrease the margin of error to 0.3

Statistics

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

A digital health startup is analyzing ECG sensor data captured from wearable heart monitors. Each row in the dataset represents one heartbeat, including its timestamp and calculated heart rate at that moment.

The clinical team wants to detect tachycardia runs, periods where a patient’s heart rate stays above 100 bpm continuously for at least 10 seconds .

Write a SQL query to identify every valid tachycardia run and return:

<ol>
<li><code>patient_id</code></li>
<li><code>run_start</code>: timestamp of the first beat in the run</li>
<li><code>run_end</code>: timestamp of the last beat in the run</li>
<li><code>duration_seconds</code>: difference in seconds between start and end (rounded to 2 decimals)</li>
</ol>

Sort results by <code>patient_id</code>, then <code>run_start</code>.

Definition of a Tachycardia Run

<ul>
<li>All consecutive heartbeats must have <code>heart_rate &gt; 100</code></li>
<li>Total duration ≥ 10 seconds</li>
<li>Any gap ≥ 3 seconds between consecutive beats breaks the run</li>
</ul>

Note: A patient may have multiple separate runs.

Schema

Input

<code>ecg_readings</code> table

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

<tbody>
<tr>
<td>patient_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>timestamp</td>
<td>DATETIME</td>
</tr>

<tr>
<td>heart_rate</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output

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

<tbody>
<tr>
<td>patient_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>run_start</td>
<td>DATETIME</td>
</tr>

<tr>
<td>run_end</td>
<td>DATETIME</td>
</tr>

<tr>
<td>duration_seconds</td>
<td>DECIMAL</td>
</tr>
</tbody>
</table>
Example

Input

<code>ecg_readings</code> table

<table>
<thead>
<tr>
<th>patient_id</th>
<th>timestamp</th>
<th>heart_rate</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>2025-03-01 10:00:00</td>
<td>98</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:02</td>
<td>105</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:04</td>
<td>110</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:07</td>
<td>108</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:12</td>
<td>107</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:15</td>
<td>85</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:20</td>
<td>120</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:28</td>
<td>122</td>
</tr>
</tbody>
</table>
Output

<table>
<thead>
<tr>
<th>patient_id</th>
<th>run_start</th>
<th>run_end</th>
<th>duration_seconds</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>2025-03-01 10:00:02</td>
<td>2025-03-01 10:00:12</td>
<td>10.00</td>
</tr>
</tbody>
</table>

<h3>Explanation</h3>

The high-rate streak from 10:00:02 to 10:00:12 forms one continuous sequence because each gap between timestamps (2 to 4, 4 to 7, and 7 to 12) is less than three seconds. This creates a valid 10-second run. The later high values at seconds 20 and 28 are separated by an eight-second gap, so they form a different sequence that is shorter than 10 seconds and is therefore ignored.

Identify tachycardia runs where heart rate stays above 100 bpm for at least 10 seconds and return run start, end, and duration

Detecting ECG Tachycardia Runs

Let’s say that you’re the PM on Google Maps.

<ol>
<li>How would you improve Google Maps?</li>

<li>What metrics would you check to see if your feature improvements are successful?</li>
</ol>

Google Maps Improvement

Product Sense & Metrics

Given that $X$ and $Y$ are independent random variables with normal distributions, what is the mean and variance of the distribution of $2X - Y$ when the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$?

Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the mean of the distribution of $2X - Y$?

Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the mean of the distribution of $2X - Y$?

Distribution of 2X - Y I

Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the variance of the distribution of $2X - Y$?

Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the variance of the distribution of $2X - Y$?

Distribution of 2X - Y II

What is the mean and variance of 2X - Y when X~N(3, 4) and Y~N(1, 4)

Distribution of 2X - Y

Probability

You are given a binary tree of unique positive numbers. Each node in the binary tree is represented as a dictionary with the following keys:

<ul>
<li><code>data</code>: integer value stored in the node</li>
<li><code>left</code>: reference to the left child (or <code>None</code>)</li>
<li><code>right</code>: reference to the right child (or <code>None</code>)</li>
</ul>

<pre tabindex="0" class="chroma"><code>node = {
 &#34;data&#34;: 6,
 &#34;left&#34;: {
 &#34;data&#34;: 3,
 &#34;left&#34;: {...},
 &#34;right&#34;: {...}
 },
 &#34;right&#34;: {
 &#34;data&#34;: 9,
 &#34;left&#34;: {...},
 &#34;right&#34;: {...}
 }
}
</code></pre>

Given two node values as input (<code>value1</code> and <code>value2</code>), write a function to return the value of the nearest common ancestor (lowest node in the tree that has both nodes as descendants).

Note: If one of the nodes doesn’t exist in the tree, return <code>-1</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code># Diagram of the binary tree
&#39;&#39;&#39;
 6 
 / \ 
 3 9 
 / \
 2 11
 / \
 5 8
&#39;&#39;&#39;
value1 = 8
value2 = 2
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>common_ancestor(root,value1,value2) -&gt; 3
</code></pre>

Explanation:

<ul>
<li>Ancestors of <code>8</code>: <code>11 → 3 → 6</code></li>
<li>Ancestors of <code>2</code>: <code>3 → 6</code></li>
<li>Common ancestors: <code>3</code> and <code>6</code></li>
<li>The nearest common ancestor is <code>3</code>.</li>
</ul>

Write a function to return the value of the nearest node that is a parent to both nodes.

Nearest Common Ancestor

Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand.

You are given a target value to search. If the value is in the array, then return its index; otherwise, return -1. 

Notes:

<ul>
<li>Rotating an array at pivot $n$ gives you a new array that begins with the elements after position $n$ and ends with the elements up to position $n$.</li>
<li>You may assume no duplicate exists in the array.</li>
</ul>

Bonus: Your algorithm’s runtime complexity should be in the order of $O(\log n)$.

Example:

Input: 

<pre tabindex="0" class="chroma"><code>sample_input = [0,1,2,4,5,6,7] 
rotated_input = [4,5,6,7,0,1,2]
target_value = 6
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def target_value_search(rotated_input, target_value) -&gt; 2
</code></pre>

Search for a value in log(n) over a sorted array that has been shifted.

Target Value Search

Imagine you are asked to build a machine learning model to decide new loan approvals for a
financial firm. You ask the data department in the company for a subset of data to get started
working on the problem. The data includes different features about applicants such as age,
occupation, zip code, height, number of children, favorite color, etc. You decide to build
multiple machine learning models to test out different ideas before settling on the best one.

How would you explain the bias-variance tradeoff with regards to
building and choosing a model to use?

Bias vs. Variance Tradeoff

Write a Python function called <code>group_anagrams</code> that takes a list of strings as input and returns a list of lists, where each inner list contains a group of anagrams that were present in the input list.

An anagram is a word or phrase formed by rearranging the letters of a different word or phrase, using all the original letters exactly once.

Note: Each of the inner lists should be ordered alphabetically and contain no duplicate values

<h3>Example:</h3>

Input:

<pre tabindex="0" class="chroma"><code>words = [&#34;eat&#34;, &#34;tea&#34;, &#34;tan&#34;, &#34;ate&#34;, &#34;nat&#34;, &#34;bat&#34;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>[ 
 [&#34;nat&#34;,&#34;tan&#34;],
 [&#34;ate&#34;,&#34;eat&#34;, &#34;tea&#34;],
 [&#34;bat&#34;]
]
</code></pre>

Explanation:

In the example, the words “eat”, “tea”, and “ate” are anagrams of each other, as are the words “tan” and “nat”. The word “bat” does not have any anagrams in the input list, and therefore is listed on its own. The function then groups the anagrams together and returns a list of lists representing these groups.

Each of the lists representing a group of anagrams is sorted in alphabetical order.

Identify the groups of anagrams in a list of words

Groups of Anagrams

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?

Given a table of user logs with platform information, count the number of daily active users on each platform for the year of 2020.

Example:

Input:

<code>events</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>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>action</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>url</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>platform</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
Output:

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

<tbody>
<tr>
<td><code>platform</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

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

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

You are given two non-empty linked lists representing two non-negative integers. Each list contains a single number, where each item in the list is one digit. The digits are stored in reverse order.

Task: Add the two numbers and return the sum as a linked list, also with the digits in reverse order. You may assume the two numbers do not contain any leading zeros, except the number 0 itself.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>l1 = 2-&gt;4-&gt;3-&gt;null
l2 = 5-&gt;6-&gt;4-&gt;null
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>addTwoNumbers(l1, l2) = 7-&gt;0-&gt;8-&gt;null
</code></pre>

Explanation: 342 + 465 = 807.

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>l1 = 0-&gt;null
l2 = 0-&gt;null
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>addTwoNumbers(l1, l2) -&gt; 0-&gt;null
</code></pre>

Explanation: 0 + 0 = 0.

In this problem, we are given two linked lists representing two non-negative integers, with each item in the list holding one digit. The digits are stored in reverse order, and each of their nodes contains a single digit. We are required to add the two numbers and return the sum as a linked list.

Radix Addition

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?



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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