Master ML Algorithms Asked in Real Interviews

Practice implementation problems asked at Google, Meta, OpenAI, Tesla, and more.

0/11 Solved

Status	Title	Companies	Tags	Difficulty	Acceptance
	1. Implement Linear Regression	Google••••••••+2	+2	Easy	78.4%
	2. Sigmoid Activation Function	Google••••••••+1	+2	Easy	89.2%
	3. Softmax Function	Google••••••••+1	+1	Easy	82.5%
	4. K-Nearest Neighbors Classifier	••••••••••••+1	+2	Medium	62.1%
	5. K-Means Clustering	••••••••••••+2	+2	Medium	68.7%
	6. Decision Tree Classifier	Google••••••••+2	+2	Hard	34.8%
	7. Cross-Entropy Loss	Google••••••••+2	+1	Medium	71.3%
	8. Batch Normalization	Google••••••••+2	+1	Medium	55.8%
	9. Principal Component Analysis	••••••••••••+2	+1	Hard	42.3%
β	10. Build a Neural Network	Google••••••••+3	+2	Hard	28.9%
	11. Matrix Multiplication	Google••••••••+1	+1	Easy	82.3%

Easy78.4%

Google

••••

Easy89.2%

Google

••••

Easy82.5%

Google

••••

Medium62.1%

••••

Medium68.7%

••••

Hard34.8%

Google

••••

Medium71.3%

Google

••••

Medium55.8%

Google

••••

Hard42.3%

••••

Hard28.9%

Google

••••

Easy82.3%

Google

••••

Practice implementation problems asked at Google, Meta, OpenAI, Tesla, and more.

0/11 Solved

Status	Title	Companies	Tags	Difficulty	Acceptance
	1. Implement Linear Regression	Google••••••••+2	+2	Easy	78.4%
	2. Sigmoid Activation Function	Google••••••••+1	+2	Easy	89.2%
	3. Softmax Function	Google••••••••+1	+1	Easy	82.5%
	4. K-Nearest Neighbors Classifier	••••••••••••+1	+2	Medium	62.1%
	5. K-Means Clustering	••••••••••••+2	+2	Medium	68.7%
	6. Decision Tree Classifier	Google••••••••+2	+2	Hard	34.8%
	7. Cross-Entropy Loss	Google••••••••+2	+1	Medium	71.3%
	8. Batch Normalization	Google••••••••+2	+1	Medium	55.8%
	9. Principal Component Analysis	••••••••••••+2	+1	Hard	42.3%
β	10. Build a Neural Network	Google••••••••+3	+2	Hard	28.9%
	11. Matrix Multiplication	Google••••••••+1	+1	Easy	82.3%