
Exploring Machine Learning Concepts
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Information Technology (IT)
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Professional Development
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machine learning
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16 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary goal of regression in machine learning?
To predict continuous outcomes based on input data.
To reduce the dimensionality of input features.
To optimize the performance of classification algorithms.
To classify categorical outcomes based on input data.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Define classification in the context of machine learning.
Classification involves clustering data points into groups without labels.
Classification is an unsupervised learning method that finds patterns in data.
Classification is a technique used for regression analysis in machine learning.
Classification is a supervised learning technique that categorizes data into predefined classes.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does a confusion matrix represent?
A confusion matrix represents the performance of a classification model by comparing predicted and actual classifications.
A confusion matrix indicates the number of features in a dataset.
A confusion matrix is used to visualize the training data of a model.
A confusion matrix shows the distribution of data points in a dataset.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Explain the concept of a decision tree.
A decision tree is a graphical representation of a random process without any data splitting.
A decision tree is a model used for classification and regression that splits data into branches based on feature values.
A decision tree is a type of neural network used for deep learning.
A decision tree is a linear model that predicts outcomes based on a single feature.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the K-Nearest Neighbors (KNN) algorithm work?
KNN predicts outcomes based on the farthest data points.
KNN requires labeled data for training only once.
KNN uses a single data point to make predictions.
KNN identifies the 'k' closest data points to make predictions based on their majority class or average value.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the importance of data cleaning in machine learning?
Data cleaning is only relevant for supervised learning.
Data cleaning only affects the speed of computation.
Data cleaning is unnecessary for model training.
Data cleaning is important because it enhances data quality, leading to better model accuracy and performance.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
List two common libraries used for numerical operations in Python.
OpenCV, Pillow
NumPy, SciPy
TensorFlow, Keras
Pandas, Matplotlib
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