1.Imbalance data
2.Missing Data
3.正则化
4.Ensemble Modeling
5.imbalanced data
6.正则化
7.Visualization
8.邮件通知
9.VIEW
10.PRIMARY KEY and FOREIGN KEY
11.WHERE and HAVING
12.What is normalization and de-normalization?
13.Join
14.T1 monthly_sales: product_id, month, sales. units..
15.Bias vs variance
16.找Customer
17.Group Anagrams
18.polynominal regression
19.covariance matrix
20.knapsack问题
21.downsample
22.downsample对Metric的影响
23.Dropout
24.分类模型类别
25.参数估计
26.高斯分布参数估计
27.Gradient Boosting
28.Ensemble Modeling
29.feature selection
30.feature selection
31.防止过拟合
32.Dropout
33.决策树
34.LSTM
35.模型分类
36.激活函数
37.PCA
38.高维数据
39.KNN
40.Loss
41.偏差硬币
42.Product of Array Except Self
43.Valid Parentheses
44.防欺诈系统设计
45.完整数据分析流程
46.异常检测
47.EM
48.模型参数与超参数
49.逻辑回归
50.线性回归假设
51.决策树
52.KNN
53.聚类
54.Duration
55.超参
56.分布解释
57.数据预处理
58.找错 改错
59.Reorganize String
60.How to do AA test to sanitycheck
61.calculate beta confidence interval
62.How do you decide how long to do ABtesting
63.Calculate the sample size. What is the formula and parameters
64.What is the process of ABtesting and what pitfal should be noted for each item
65.Improve the accuracy of an experimentation
66.What's statistical power?
67.Explain Selection bias
68. Explain Bias variance tradeoff
69.Difference between Clustering vs. classification
70.In what scenarios you want to change that threshold?
71.Combinations of travel 50 states
72.薪资排列
73.SQL
74.Measuring impact with no AB test
75.Define LastMile
76.Design a controller for traffic lights
77.msg
78.Probability
79.ANOVA
80.Definition of Causal inference
81.Definition of Bayesian theorem
82.Definition of Central limit theorem
83.Focus of climate pledge
84.Leetcode 15
85.Find the maximum greyness
86.Delete linked list node
87.Dimension and measure
88.Visualize ordinal categorical data
89.Difference between histogram and bar chart
90.LeetCode146
91.What's the key metrics to measure the performance of logistic regression? "
92.SQL window function
93.SQL nested query
94.SQL case when
95.SQL window function
96.SQL aggregation function
97.SQL aggregation function
98.SQL 的joins 与case
99.人口运算的问题
100.Regular expression中substring的用法
101.数列的顺序变换以及运算
102.对array的运算，比如最大到最小的差值
103.求中位数
104.扔骰子N次概率
105.General AB Testing process
106.Design dashboard
107.Investigate the fall of company's performances
108.Descibe p-value non-technically
109.Tradeoff between variance and bias
110.Sampling
111.Experiment design
112.Estimate whether regression model works
113.一个产品的实际revenue比predicted revenue低40%， 问如何找原因
114.Product sense question
115.Amazon Seller Product Rating Analysis
116.Minimum Sum for Non-Decreasing Server Power
117.Maximize Reward Points
118.Find the Count of Strings with Most Vowels at the Beginning
119.Probability Questions and Online Learning Algorithm
120.Grouping Array Elements with Maximum Gap
121.Filling Problem with Array and Quota
122.Root Cause Analysis in Work
123.Product Market Fit Analysis
124.Login Data Analysis with SQL
125.Package Allocation Optimization Model
126.Dashboard Visualization Explanation
127.Knowledge of Fundamentals Outside Your Field
128.Research Depth Discussion
129.Longest Common Subsequence Problem
130.Find the Longest Path for an Amazon Warehouse Robot
131.Write Code for the APIs for the Game Blackjack
132.Simulation Modules
133.Coding Practice
134.Get outliers value
135.Get maximum category max count
136.SQL Query Writing
137.SQL Basic Concepts
138.Count Dominant Substrings in a String
139.Calculate Total Scores for AI Software
140.Machine Learning Models Application Scenarios
141.Basic Machine Learning Trade-offs
142.Suitable Warehouse Location
143.Minimum Watch Score
144.Amazon SQL Challenge Preparation
145.Differences Between Ensemble Learning Methods
146.Improve the Bar Chart Visualization
147.Find Popular Movies and TV Shows by Continent
148.Extract and Combine Movies and TV Shows
149.Calculate the most popular show's duration
150.Matrix Compression Utility
151.DNA Anagram Pattern
152.Case Study: Building a Chatbot for Customer Service
153.Model Recommendation for Embedding
154.Transformer Architecture
155.Synthetic Sample Generation
156.Solving Sample Imbalance
157.Overfitting Due to Data Samples
158.Preventing Overfitting in Neural Networks
159.Bias vs Variance in Models
160.Explain the role of a senior data scientist in a project
161.Server Request Handling
162.Maximum Number of Negative Integers in Array with Positive Prefix Sums
163.Window Functions for Finding Median
164.SQL Joins and Their Differences
165.Calculating Age from Date of Birth
166.SQL Table Deletion
167.DNA Anagram Pattern
168.Compute Encoded Product Name
169.Maximize Total Area of Rectangles
170.Employee Skill Pair Sum
171.Describe a situation where you had to dive deep to find the root cause of a problem.
172.Minimizing Truck Load
173.Discriminative vs. Generative Models
174.Classification and Clustering Algorithms
175.Supervised vs. Unsupervised Learning
176.Optimization with Gradient Descent
177.Dimensionality Reduction Techniques
178.A/B Testing Methodology
179.Bagging vs. Boosting
180.Explain the Bias-Variance Tradeoff
181.Maximum Number of Balanced Shipments
182.Make Power Non-Decreasing
183.Machine Learning Data Splitting
184.Optimal Delivery Center Location
185.Server Stability Calculation
186.Design a Data Dashboard for Performance Evaluation
187.Optimize SQL Query
188.Data Visualization for Uber App Attributes
189.SQL Query Using Window Functions, GROUP BY, and HAVING
190.Warehouse Location Selection
191.Lottery System Probability
192.Analyze User Website Visit Pattern
193.Minimum Errors in a Binary String
194.Reduce Gifts
195.Weather Data Statistical Display
196.Control and Planning Problem Integration
197.Maximum Sum Path in a Binary Tree with Negative Values
198.Find the Kth Largest Element in an Array
199.Maximum Score in a Letter Game
200.Continuous User Access Identification
201.Array Sum Combination
202.ML System Design: Recovering Deleted Product Descriptions
203.ML Breadth: Explain unfamiliar theories in simple terms
204.ML Depth: Discuss a project in detail
205.Coding Interview Question
206.SQL Problem Solving
207.Detailing an Impactful ML Project
208.Designing a Tableau Dashboard for Uber
209.Optimizing SQL with LEFT JOIN
210.Explain CROSS JOIN with an example
211.What is DML?
212.What is DDL?
213.Explain the model you were responsible for from data preparation to deployment.
214.SQL Join with Varchar ID Comparison
215.Sequence Partitioning Based on Maximum Value Criteria
216.Prefix Sum and Postfix Sum Calculation
217.Minimum Pages to Read Per Day
218.What is sharding and how does it work?
219.Explain the differences and applications of relational and non-relational databases.
220.Data Visualization Discussion
221.SQL Knowledge Evaluation
222.Python CSV File Processing Without Pandas
