
Data Science and Machine Learning (Theory and Projects) A to Z - Why Machine Learning: Why Machine Learning is Trending
Interactive Video
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Information Technology (IT), Architecture, Social Studies
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University
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Practice Problem
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Hard
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is a large amount of data crucial for machine learning algorithms?
It helps in reducing the cost of computation.
It allows algorithms to learn patterns and make accurate predictions.
It ensures data privacy and security.
It speeds up the training process significantly.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What technological advancement has contributed to the increased availability of data?
Advancements in battery technology.
Deployment of numerous sensors and mobile technology.
Development of new programming languages.
Introduction of high-speed internet.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a key factor that allows machine learning algorithms to handle large datasets effectively?
Availability of high computational power and advanced hardware.
Increased number of data scientists.
Use of traditional computing methods.
Reduction in data size.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What role does cloud computing play in machine learning?
It decreases the accuracy of predictions.
It provides virtual machines for high-performance tasks.
It eliminates the need for algorithms.
It reduces the need for data.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a reason for the boom in machine learning?
Availability of large datasets.
High computational power.
Stable software stacks.
Decrease in global internet usage.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which software package is mentioned as part of the stable software stack for machine learning?
TensorFlow
Java
Microsoft Word
Adobe Photoshop
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the expected trend for machine learning in the future?
It will become obsolete.
It will continue to grow and increase.
It will remain stagnant.
It will decline rapidly.
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