1.Deep Learning Explained Simply for Kids
2.Types of Neural Networks: An Overview
3.Customer Tracking Using Camera Footage
4.Dealing with December Customer Churn: What to Do?
5.Optimizing Budget Allocation for Multi-Platform Advertising.
6.leetcode833
7.Customer Service Analytics Queries: 30-Day Metrics Analysis
8.Optimizing Help Articles for Apps: Metrics and Prioritization.
9.Sudden 7% Drop in Metrics: What Caused It?
10.Calculating the p-value of binomial distribution.
11.Harrassment处理
12.How to measure the success of a new feature
13.客户健康指数
14.Parse link
15.Recommendation system
16.Evaluate model missing performance
17.Normal Distribution基础
18.Unsupervised Learning
19.MIssing Value
20.建模的数据处理
21.建模的准备工作
22.Frequentist vs Bayesian
23.Simpson Paradox
24.Reverse Words in a String
25.string操作
26.leetcode935
27.Wildcard Matching
28.股票价格预测
29.飞机起飞顺序
30.Remove K Digits
31.Count Primes
32.Best Time to Buy and Sell Stock
33.Valid Palindrome II
34.String切割
35.Sort Colors
36.Roman to Integer
37.Move Zeroes
38.Merge Intervals
39.价格预测
40.Verifying an Alien Dictionary
41.Sort Characters By Frequency
42.Kth Largest Element in an Array
43.Random Pick with Weight
44.Equal Sum Arrays With Minimum Number of Operations
45.Minimum Deletions to Make Character Frequencies Unique
46.组合
47.Describe deep learning to a 5-year-old
48.Favorite area in DS
49.Describe a Data Science Project
50.如何寻找outlier
51.design a cab sharing service
52.How to predict users' rating
53.设计一个ads recommendation system
54.时间序列模型
55.GBDT
56.loss function
57.回归树和决策树
58.决策树的最优切分变量
59.基础算法
60.定调表操作
61.如何判断系统更新是否成功
62.Bayes' Theorem
63.Win the game
64.Bagging or boosting
65.L1/L2 regularizations
66.How would you deal with Overfitting?
67.Regressoin and GBT model
68.Bias and variance
69.Loss function
70.Logistic regression vs linear regression
71.Central Limit Theory and Law of large number
72.TypeI and TypeII error
73.Different distributions
74.通俗地解释confusion matrix
75.Precision vs recall
76.能否用accuracy来measure performance of a binary classification model
77.Overfitting基本定义与解决方法
78.Bagging vs Boosting
79.False positive vs false negative
80.Confidence Interval是什么
81.How to deal with missing values
82.数据清洗的基本步骤
83.通俗地解释p_value
84.Gradient decent vs gradient boosting
85.Decision tree
86.Novel effect
87.预测网站浏览量
88.K-means
89.How to determine whether a new feature should be launched
90.feature过多该怎么办
91.通俗地解释p_value
92.Merge Array
93.如何处理feature过多的问题
94.TF-IDF
95.RNN模型
96.LeetCode 1587
97.Finding credit card information
98.LeetCode1882
99.Def function
100.三轮骰子游戏
101.Logistics regression
102.3 ants
103.Unfair coin
104.客户的健康指数
105.100! vs 10^100
106.Calculate CTR
107.Car dealer
108.Learning rate
109.Deep NN
110.判断网页语言
111.Device table
112.Salary
113. Max k value
114.Shuffled
115.Bipartite graph
116.Probability: Family children
117.New feature是不是successful
118.Model and performance
119.Missing value imputation
120.将整数输出成string
121.病人table
122.Count sales
1. Deep Learning Explained Simply for Kids
Explain deep learning to a child
2. Types of Neural Networks: An Overview
3. Customer Tracking Using Camera Footage
4. Dealing with December Customer Churn: What to Do?
在某个12月看到很多customer churn，问这个情况怎么办
5. Optimizing Budget Allocation for Multi-Platform Advertising.
如果你向很多平台投放广告，但是你有一个budget，你怎么能知道，你的budqet怎么向这些平台分配。
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