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| Section | Objectives |
|---|---|
| Topic 1: Machine Learning Models | - Supervised learning models
|
| Topic 2: Advanced Topics | - MLOps concepts
|
| Topic 3: Data Preparation and Feature Engineering | - Feature engineering
|
| Topic 4: Model Evaluation and Optimization | - Model tuning
|
| Topic 5: Machine Learning Engineering and Deployment | - Deployment considerations
|
| Topic 6: Machine Learning Foundations | - Mathematical and statistical fundamentals
|
Question 1
What is Principal Component Analysis (PCA) a technique used for in unsupervised learning?
Response:
A. Reducing the dimensionality of data
B. Clustering similar data points
C. Improving the accuracy of classification models
D. Predicting future trends in data
Question 2
What is a common use of CNNs in image processing?
Response:
A. Audio signal processing
B. Sequence prediction
C. Feature extraction
D. Data storage optimization
Question 3
What is the purpose of inferential statistics in machine learning?
Response:
A. To visualize complex datasets
B. To make predictions about a population based on a sample
C. To describe the basic features of data
D. To classify data into different categories
Question 4
What is the main use of the NumPy library in Python for machine learning?
Response:
A. Handling large arrays and matrices
B. Data visualization
C. Web scraping
D. Text processing
Question 5
Which techniques can help prevent overfitting in Convolutional Neural Networks?
(Choose two)
Response:
A. Max pooling
B. Dropout
C. Early stopping
D. Increasing the number of convolutional layers
Solutions:
| Question 1 Answer: A | Question 2 Answer: C | Question 3 Answer: B | Question 4 Answer: A | Question 5 Answer: B,C |
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