1. Implement K-means from Scratch
Implement K-means clustering algorithm from scratch. Additionally, address the following related questions: How would you initialize clusters? How would you choose the number of clusters? How can K-means be made efficient when dealing with large amounts of data?
2. Design a Text NLP Tool
How would you design a text NLP (Natural Language Processing) tool?
3. Explain the concept of k-means clustering and implement it.
During the interview, you are asked to explain the concept of k-means clustering. After explaining, you are then tasked with implementing the algorithm. Due to time constraints, you are also asked to discuss how you would proceed further if given more time.
4. Reinforcement Learning in Recommendation Systems
Discuss the application of Reinforcement Learning (RL) in recommendation systems.
5. Deep Learning Basics: CNN
Discuss the basic concepts of Convolutional Neural Networks (CNNs).
