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Data Structures & Algorithms

Find the missing integer from a array of consequtive integers

Find the Missing Number

Given a dictionary consisting of many roots and a sentence, write a function to stem all the words in the sentence with the root forming it.

Replace Words with Stems

Given the root node, verify if a binary search tree is valid or not.

Binary Tree Validation

What is the difference between the loc and iloc functions in pandas DataFrames?

loc vs iloc

Machine Learning

Bias vs. Variance Tradeoff

Let's say that you're training a classification model.   How would you combat overfitting when building tree-based models?

Overfit Avoidance

Brainteasers

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

Your Strengths and Weaknesses

Statistics

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

Bootstrapping Samples

When an interviewer asks a question along the lines of:

<ul>
<li>What would your current manager say about you? What constructive criticisms might he give?</li>
<li>What are your three biggest strengths and weaknesses you have identified in yourself?</li>
</ul>

How would you respond?

When asked about your strengths in an interview, what is an effective way to respond?

When asked about your strengths in an interview, what is an effective way to respond?

Your Strengths and Weaknesses I

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Your Strengths and Weaknesses II

Let’s say that you’re training a classification model.

How would you combat overfitting when building tree-based models?

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?

<h1>Binary Tree Validation</h1>

You are given the root of a binary tree. You need to determine if it is a valid binary search tree (BST).

A valid BST is defined as follows:

<ul>
<li>The left subtree of a node contains only nodes with values less than or equal to the node’s value.</li>
<li>The right subtree of a node contains only nodes with values greater than or equal to the node’s value.</li>
<li>Both the left and right subtrees must also be binary search trees.</li>
</ul>

Given the function <code>def is_valid_bst(root: Node) -&gt; bool:</code>, return True if the binary tree is a valid BST. Otherwise, return False.

<h3>Example:</h3>

Input:

<img src="/s3/questions/9664817c-3e12-4a40-9236-8382b13f55a0.png" alt="image"/>Converted Binary Tree.png

Output:

<pre tabindex="0" class="chroma"><code>def is_valid_bst(Node(3)) -&gt; True
</code></pre>

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>

What does it mean to “bootstrap” a data set?

Give an example of a time when it would be appropriate to bootstrap a smaller sample(s) from a larger data set.

What are the advantages and disadvantages of doing so?

In data science, there exists the concept of stemming, which is the heuristic of chopping off the end of a word to clean and bucket it into an easier feature set. 

Given a dictionary consisting of many roots and a sentence, write a function <code>replace_words</code> to stem all the words in the sentence with the root forming it. If a word has many roots that can form it, replace it with the root with the shortest length.

Example:

Input:

<pre tabindex="0" class="chroma"><code>
roots = [&#34;cat&#34;, &#34;bat&#34;, &#34;rat&#34;]
sentence = &#34;the cattle was rattled by the battery&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code> &#34;the cat was rat by the bat&#34;
</code></pre>

What is the difference between the <code>loc</code> and <code>iloc</code> functions in <code>pandas</code> DataFrames?

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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