1.Generating sorted output using f(x) with a sorted list
2.Effective Customer Segmentation Strategies for Business Travelers
3.Visualizing LI Friend Connections and Analyzing Central Tendency
4.Visualizing Height Distribution in America: Men vs Women
5.Predicting User Hires using Imbalanced, Regularized, and Tree-based Models
6.Calculating Variance and Proportions with Large Datasets
7.Properties of a Set of Correlated Variables X1...XP
8.Handling Imbalanced Data: Downsample and Upsample Techniques
9.Simulating Dice Roll Probability Distribution with my_function(p)
10.Identifying Business Travelers in COVID Era: Data Collection and Follow-up
11.Choosing the Dynamic Distribution of Two Bank Branches' Five Tellers
12.为Python实现代码
13.N-sided Dice Probability Function
14.1. Regularized Loss Function for Linear Model 2. Validating the Model Created from Sampling Big Data 3. Overcoming Imperfect Salary Data for Analysis 4. Choosing a Linear Model for Imperfect Data
15.Eliminating Duplicate Elements in Merged Lists with O(N) Time Complexity
16.Product of Array Except Self in Linear Time
17.Defining Overfitting and Underfitting: Coping with Overfitting
18.Explaining Decision Trees, Random Forests and Gradient Boosting: Feature Importance Calculation and Information Entropy
19.Two CSV files with Clicks and Assignments Data
20.Flawed Logic in Coin Toss Bet
21.Job Posting Analysis: New, Repeat, Reactivated Posts.
22.Measuring Bay Area Income: Choosing Metrics for Analysis
23.Analyzing the Drop in Job Application Volume.
24.Designing A/B Testing for Multiple Email Formats
25.Diagnosing the Case of a Dropped Job Application
26.Exploring the Trade-off Between Bias and Variance
27.Understanding Overfitting and Underfitting in Machine Learning
28.Correcting Overfitting: Techniques and Strategies.
29.Bagging vs. Boosting: Understanding the Key Differences
30.Understanding Gradient Descent: An Overview
31.Best Matrices for Binary Classification Model?
32.Recall and Precision Explained
33.Understanding AUC: Measuring Model Performance in Analytics
34.Comparing Variance of Bootstrap Sampling: median vs 95%
35.Assessing Assumption That Customers Ignore Ads After 5th View
36.Analyzing Decreased Physical Store Sales and Traffic
37.Can Lasso be solved using Linear Programming? If not, how to adjust?
38.Counting Pairs with Sum Below a Given Value
39.how could you improve linkedin
40.member ld
41.Lowest Common Ancestor of Deepest Leaves
42.SQL query
43.AB Test
44.CDF and probability
45.SQL window function
46.排列组合问题
47.Business travel question
48.Distirbution
49.Multimodal distribution
50.SQL query
51.排列组合
52.Sample data ml building
53.SQL aggregation funciton
54.Tradeoff
55.Measure changing search results from list to box
56.SQL aggregation functions
57.AB Test
58.Job application rate changes
59.P-value expaination
60.AB Test - novelty effect
61.AB Test
62.LinkedIn Feed ML Design
63.Expectation-Maximization (EM) Algorithm
64.Mean and Covariance Equations
65.Monotonic List Transformation
66.Partition Array into K Equal Sum Subsets
67.SQL Query to Compare Video Posting Activity
68.SQL Query for Video Posts by Country
69.SQL Query for User Activity on the Same Day
70.Identifying Business Travelers
71.SQL Notification On/Off
72.Ad Click Prediction System Design
73.Design a Ranking Model
74.Machine Learning Basics
75.Machine Learning Design for Job Recommendation
76.XGBoost and Decision Trees
77.Underfitting vs Overfitting in Machine Learning
78.Find All Repeated DNA Sequences of Length 10
79.Logistic Regression and Overfitting/Underfitting
80.Optimal Point on a Line
81.Design an Ads Recommendation System
82.Probability calculation for bus arrival times
83.Design 'People You May Know' Feature
84.Design a Recommendation System
85.Imbalanced Data: XGB vs Random Forest
86.Simpson's Paradox Decision Making
87.Biased Coin Random Number Generation
高频题（0）
