Data Science Interview Questions – ML Introduction
Q1. (Asked in Infosys System Engineer Interview)
What is Machine Learning?
Answer:
Machine Learning (ML) is a subset of Artificial Intelligence (AI) that allows systems to learn from data and improve their performance without being explicitly programmed. It helps machines make decisions based on patterns.
Q2. (Asked in TCS Digital Interview)
Why is Machine Learning important today?
Answer:
ML helps automate tasks, make predictions, and improve user experiences. It powers real-world applications like fraud detection, personalized recommendations, voice assistants, and self-driving cars.
Q3. (Asked in Cognizant GenC Next Interview)
What are the main types of Machine Learning?
Answer:
- Supervised Learning – Uses labeled data (e.g., spam detection)
- Unsupervised Learning – Uses unlabeled data (e.g., customer segmentation)
- Reinforcement Learning – Learns through rewards and penalties (e.g., game bots)
Q4. (Asked in Wipro Data Science Interview)
Give a real-life example of Machine Learning.
Answer:
Netflix recommending movies based on your watch history is an example of supervised learning using user preferences and past behavior.
Q5. (Asked in Capgemini Analyst Role)
What is the difference between AI, ML, and Deep Learning?
Answer:
- AI: The broad field of making machines smart
- ML: A part of AI that learns from data
- Deep Learning: A subset of ML that uses neural networks with many layers
Q6. (Asked in HCL Technologies Interview)
What are some common Machine Learning algorithms?
Answer:
- Linear Regression
- Logistic Regression
- Decision Trees
- k-Nearest Neighbors (k-NN)
- Random Forest
- Support Vector Machines (SVM)
Q7. (Asked in Deloitte USI Interview)
What is training data and testing data?
Answer:
- Training Data is used to teach the model.
- Testing Data is used to evaluate how well the model learned.
It ensures that the model works well on unseen data.
Q8. (Asked in Tech Mahindra Interview)
What industries use Machine Learning?
Answer:
ML is used in:
- Healthcare – Disease prediction
- Finance – Fraud detection
- Retail – Customer insights
- Agriculture – Crop monitoring
- Manufacturing – Predictive maintenance
Q9. (Asked in IBM Associate Analyst Interview)
What is a machine learning model?
Answer:
A machine learning model is a mathematical structure trained on data to recognize patterns and make decisions or predictions based on new inputs.
Q10. (Asked in Amazon Applied Scientist Intern Interview)
What skills are needed to get started with Machine Learning?
Answer:
- Basic knowledge of Python or R
- Understanding of math and statistics
- Familiarity with data handling tools (e.g., Pandas, NumPy)
- Curiosity to experiment and solve problems
