1.Designing a Binary Classifier for GPT-generated Answers
2.Document Selection for Questions
3.Write a logistic regression from scratch
4.Machine Learning Knowledge
5.Basic Python questions
6.Explain the principle and application scenarios of random forest
7.Discuss the details of logistic regression
8.Combinations of Four-Wheeled and Two-Wheeled Vehicles
9.Binary Representation for Power of Two
10.Describe an instance where you were required to gather and analyze data from various sources to make an informed decision.
11.Chess Tournament
12.Reduce the Array
13.Find the Total Cost to Reduce the Array to a Single Element
14.Probability and Finance Knowledge
15.Statistical Modeling Related Questions
16.Game Winner
17.Almost Equivalent Strings
18.Rearranging a Word
19.Fun with Anagrams
20.Sum of All Subarrays
21.Ideal Number Count Within a Range
22.Probability Problem with Coin Flips
23.Correlation Matrix Characteristics
24.Business Case: Fraud Detection
25.Word Embedding and Transformer Structure
26.Bayesian Statistics
27.Stochastic Gradient Descent (SGD)
28.Principal Component Analysis (PCA)
29.L1 and L2 Regularization
30.Lottery Coupons
31.Probability Questions from the Green Book
32.Linear Regression Matrix Expression and QR Decomposition Optimization
33.Random Processes from the Green Book
34.Digit Sum Matching
35.Count Numbers with No Repeating Digits
36.Almost Equivalent Strings
37.Triangle Area Calculation
38.Calculate Score Difference
39.Stock Price Average Calculation
40.Understanding Weighted Average Cost of Capital (WACC)
41.Portfolio Construction for Minimizing Volatility Correlation
42.Hedging Vega
43.Understanding of Options and Delta Hedging
44.What is Ito Integral and what does a Weiner process's Ito Integral look like?
45.Basic options problem
46.Bayesian probability problem with 1000 coins, one of which is double-headed
47.What are the steps for data validation and cleaning?
48.What are the components of assets and liabilities in a bank, and how do interest rate changes affect them?
49.What is stationarity and how do you test for it?
50.Pessimistic and Optimistic Locking in MySQL
51.Describe linear regression and explain back propagation, cost function, and how to obtain the predicted value.
1. Designing a Binary Classifier for GPT-generated Answers
Given some questions and GPT-generated answers, how would you design a binary classifier to determine which answers are hallucinations?
2. Document Selection for Questions
Given 1000 documents and some questions, how would you select 50 documents to answer these questions?
3. Write a logistic regression from scratch
Write a logistic regression from scratch.
4. Machine Learning Knowledge
Questions were asked about machine learning knowledge, specifically comparing random forests (RF) and gradient boosting trees (GBT), and discussing the variance-bias trade-off.
5. Basic Python questions
Discuss the differences between tuples and lists in Python, and how to rename or delete columns in pandas.
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