1. What is Machine Learning?
A. A type of hardware
B. A subset of artificial intelligence
C. A programming language
D. A database system
Answer: B
2. Which language is most commonly used for Machine Learning?
A. Java
B. Python
C. PHP
D. HTML
Answer: B
3. What type of learning uses labeled data?
A. Supervised Learning
B. Unsupervised Learning
C. Reinforcement Learning
D. Deep Learning
Answer: A
4. Which type of learning finds patterns in unlabeled data?
A. Supervised Learning
B. Unsupervised Learning
C. Reinforcement Learning
D. Regression
Answer: B
5. Which algorithm is used for classification problems?
A. Linear Regression
B. Logistic Regression
C. Clustering
D. Dimensionality Reduction
Answer: B
6. Which algorithm is used for predicting continuous values?
A. Linear Regression
B. K-Means
C. Decision Tree
D. Random Forest
Answer: A
7. What is a dataset?
A. A set of instructions
B. A collection of data
C. A programming language
D. A type of model
Answer: B
8. What is training data?
A. Data used to build the model
B. Data used to test the model
C. Data used to store results
D. Data used to delete models
Answer: A
9. What is test data?
A. Data used for training
B. Data used to evaluate the model
C. Data used for storage
D. Data used for programming
Answer: B
10. Which algorithm is commonly used for clustering?
A. Linear Regression
B. K-Means
C. Logistic Regression
D. Decision Tree
Answer: B
More Beginner ML Quiz Questions
11. What does ML stand for?
A. Machine Learning
B. Main Language
C. Machine Logic
D. Model Learning
Answer: A
12. Which library is commonly used for ML in Python?
A. NumPy
B. Pandas
C. Scikit-learn
D. All of the above
Answer: D
13. What is overfitting?
A. Model learns data too well including noise
B. Model performs poorly on training data
C. Model ignores data
D. Model deletes data
Answer: A
14. What is underfitting?
A. Model too complex
B. Model too simple
C. Model perfect
D. Model random
Answer: B
15. Which algorithm is based on decision rules?
A. Decision Tree
B. Linear Regression
C. KNN
D. PCA
Answer: A
16. What does AI stand for?
A. Automated Internet
B. Artificial Intelligence
C. Advanced Interface
D. Artificial Internet
Answer: B
17. Which ML method is used in recommendation systems?
A. Clustering
B. Collaborative filtering
C. Linear regression
D. PCA
Answer: B
18. What is feature in ML?
A. Output variable
B. Input variable
C. Algorithm
D. Model
Answer: B
19. What is label in ML?
A. Input data
B. Output data
C. Feature
D. Algorithm
Answer: B
20. Which ML algorithm is based on nearest neighbors?
A. KNN
B. SVM
C. Decision Tree
D. Random Forest
Answer: A
Intermediate Beginner Quiz Questions
21. What does K in KNN stand for?
A. Key
B. Kernel
C. Number of neighbors
D. Knowledge
Answer: C
22. Which technique reduces data dimensions?
A. PCA
B. Regression
C. Clustering
D. Classification
Answer: A
23. Which algorithm combines multiple decision trees?
A. Random Forest
B. Logistic Regression
C. KNN
D. Linear Regression
Answer: A
24. Which ML technique predicts categories?
A. Classification
B. Clustering
C. Regression
D. PCA
Answer: A
25. Which technique predicts numbers?
A. Classification
B. Regression
C. Clustering
D. Reinforcement
Answer: B
26. What is deep learning?
A. Type of neural network learning
B. Database system
C. Programming language
D. Storage system
Answer: A
27. What is neural network inspired by?
A. Human brain
B. Internet
C. Database
D. Computer chips
Answer: A
28. Which algorithm is popular for classification?
A. SVM
B. PCA
C. K-Means
D. Apriori
Answer: A
29. What is model accuracy?
A. Speed of model
B. Correct predictions percentage
C. Memory usage
D. Storage capacity
Answer: B
30. What is confusion matrix used for?
A. Evaluate classification models
B. Store data
C. Train models
D. Visualize datasets
Answer: A
Final Machine Learning Quiz Questions
31. What is data preprocessing?
A. Cleaning and preparing data
B. Deleting data
C. Visualizing data
D. Storing data
Answer: A
32. Which ML technique groups similar data?
A. Clustering
B. Regression
C. Classification
D. Reinforcement
Answer: A
33. What is reinforcement learning based on?
A. Rewards and penalties
B. Labels
C. Clusters
D. Regression
Answer: A
34. What is model training?
A. Teaching model using data
B. Storing model
C. Deleting model
D. Compressing model
Answer: A
35. What is prediction in ML?
A. Guessing future outcome using model
B. Deleting data
C. Compressing data
D. Storing data
Answer: A
36. Which ML algorithm is supervised?
A. Linear Regression
B. K-Means
C. PCA
D. Apriori
Answer: A
37. Which is unsupervised algorithm?
A. K-Means
B. Linear Regression
C. Logistic Regression
D. Decision Tree
Answer: A
38. Which library is used for deep learning?
A. TensorFlow
B. Matplotlib
C. Seaborn
D. Excel
Answer: A
39. What is dataset split used for?
A. Training and testing
B. Storage
C. Deleting data
D. Formatting
Answer: A
40. Which step comes after model training?
A. Model evaluation
B. Data collection
C. Data cleaning
D. Feature selection
Answer: A
Last 10 Questions
41. What is bias in ML?
A. Error due to simple model
B. Storage issue
C. Data size
D. Programming error
Answer: A
42. What is variance in ML?
A. Model sensitivity to training data
B. Data deletion
C. Storage size
D. Programming bug
Answer: A
43. Which tool visualizes data?
A. Matplotlib
B. TensorFlow
C. Keras
D. PyTorch
Answer: A
44. What is model deployment?
A. Using model in real application
B. Training model
C. Deleting model
D. Storing model
Answer: A
45. Which company created TensorFlow?
A. Google
B. Amazon
C. Microsoft
D. Facebook
Answer: A
46. Which company developed PyTorch?
A. Meta (Facebook)
B. Google
C. Amazon
D. IBM
Answer: A
47. What is big data?
A. Large datasets
B. Small data
C. Database error
D. Programming language
Answer: A
48. What is feature engineering?
A. Creating useful input variables
B. Deleting features
C. Storing data
D. Formatting data
Answer: A
49. What is hyperparameter?
A. Parameter set before training
B. Output variable
C. Data type
D. Model prediction
Answer: A
50. What is machine learning mainly used for?
A. Making predictions from data
B. Storing data
C. Formatting text
D. Creating websites
Answer: A
Conclusion
In conclusion, this Machine Learning Basics Quiz helps reinforce the fundamental concepts of machine learning, including key terms, basic algorithms, and how machines learn from data. By attempting these questions, beginners can evaluate their understanding of essential ideas such as supervised and unsupervised learning, datasets, models, and predictions.
Building a strong foundation in these basics is an important first step toward exploring more advanced topics in machine learning and artificial intelligence. Continuous practice, curiosity, and hands-on experimentation with real datasets will further strengthen your skills and confidence in this field.
Keep learning, keep experimenting, and enjoy your journey into the world of machine learning!
