ML Interview Practice

ML Interview Practice

ML Interview Practice

S.N.	Problem	Level	Status
1	Estimate Classifier Error I	Easy
2	Probability of Boy	Easy
3	Simulate a Biased Coin	Easy
4	Ant Collisions on equilateral Triangle	Medium
5	Randomly Sample a data point from a PDF	Medium
6	Generate Random numbers between 1-12	Hard
7	Estimate Minimum Number of Red Balls	Medium
8	Who will win the game	Hard
9	Double the Number	Medium
10	Median Greater than 2	Medium
11	Probability of Actual Spam	Medium
12	Replace School Principal	Medium
13	Unfair Coin Probability	Hard
14	Excpected Number of dice throw	Medium
15	Win A Lottery	Hard

S.N.	Problem	Level	Status
1	Explain Mathematical details of Linear Regression Model	Medium
2	Why do we optimize Least square cost function in Linear Regression	Hard
3	Explain Mathematics of Logistic Regression model	Medium
4	Derive logistic Regression cost function using MLE	Hard
5	Explain how will you evaluate a clustering algorithm	Medium
6	Explain how decision tree works	Medium
7	Explain Concept of Entropy in Decision Tree	Medium
8	Explain Concept of Information Gain in Decision Tree	Medium
9	Explain how Random Forest Algorithm works	Medium

S.N.	Problem	Level	Status
1	Find Minima of convex Function using Gradient Descent	Easy
2	Code Linear Regression Algorithm	Medium
3	Code Logistic Regression Algorithm	Medium
4	Code Decision Tree Algorithm	Hard
5	Code Neural Network with one hidden Layer	Hard
6	Implement Beam Search	Hard

S.N.	Problem	Level	Status
1	Code K-Means Algorithm	Easy
2	1D clustering with deterministic clusters in O(N^2)	Medium
3	1D clustering with deterministic clusters in O(N)	Hard

S.N.	Problem	Level	Status
1	N samples from a distribution	Medium
2	Sample a point randomly from a Circle of radius R	Medium
3	Reservoir Sampling	Medium
4	Estimate Expected number of Unique data points in a bootstrap sample	Hard

S.N.	Problem	Level	Status
1	Shuffle an Array	Medium
2	Moving Average of Stream data	Medium
3	Mean and variance of Stream data	Medium
4	Huffman Encoding	Medium
5	Implement rand10() using rand7()	Medium
6	Geometric Median	Medium
7	Find K Nearest 2-D Points (x,y) from Origin in a Stream of 2D data	Medium
8	Median of Stream	Hard