30 Questions
What is the primary focus of data science?
Extracting insights and knowledge from data
What does data science involve?
A combination of skills and knowledge from various fields
What can models extracted from data be used for?
Developing predictive maintenance systems
In which fields can data science be applied for customer-related purposes?
Company/banking/insurance and digital marketing
What kind of techniques are used in data science?
Statistical and computational techniques
Why is discerning relevant information increasingly critical in today's society?
To extract insights and knowledge from data
What is the main purpose of data mining?
Summarize a massive database to facilitate decision making
What is the primary task in the data cleaning phase of the data science workflow?
Removing duplicate data
In which stage of the data science workflow is the train-test data approach used?
Data modelling
What is the purpose of KDD (Knowledge Discovery from Databases) in data science?
Extraction of patterns of information from large amounts of data
What types of databases can Data Mining techniques be applied to?
Relational, spatial, temporal, documentary, multimedia databases
Which stage of the data science workflow involves building a hypothesis model for future predictions?
Data modelling
What is the focus of the optimization and deployment stage in the data science workflow?
Checking the accuracy and optimizing the model for better predictions
What is one type of data that can be included in the data collection phase?
Videos
What is the primary focus of semantic segmentation?
Assigning a label to each pixel in an image
Which dataset is commonly used for semantic segmentation?
PASCAL VOC (2012)
What are some applications of semantic segmentation?
Autonomous navigation
What does semantic segmentation contribute to scene understanding?
It assists in identifying and labeling each pixel in an image
Before the advent of deep learning, which techniques were commonly used for semantic segmentation?
TextonBoost and TextonForest
What is the difference between instance segmentation and semantic segmentation?
Instance segmentation focuses on labeling each pixel, while semantic segmentation focuses on recognizing objects.
In the context of Fully Convolutional Networks (FCN), what is the purpose of utilizing skip-layer concept?
To improve the segmentation accuracy
What is the main purpose of using deconvolutional layers in the context of semantic segmentation?
To increase the spatial resolution
Which architecture uses VGG architecture and has no fully connected (FC) layer in the context of semantic segmentation?
SegNet
What is the purpose of unpooling layers in semantic segmentation?
To recover spatial information lost during pooling
What is the primary function of U-Net architecture in the context of convolutional networks?
Biomedical image segmentation
Which technique is used in Fully Convolutional Networks (FCN) to interpret fully connected (FC) layers as convolutional layers?
Applying deconvolutional layers
What is the main difference between FCN with 1-skip connection and FCN with 2-skip connections?
The amount of spatial information used in segmentation
Which network architecture uses pre-trained networks for classification for segmentation in Fully Convolutional Networks (FCN)?
VGG
What is the purpose of utilizing deconvolutional layers in semantic segmentation?
To increase the spatial resolution
Which network architecture uses the skip-layer concept to improve the segmentation accuracy?
Fully Convolutional Networks (FCN)
Test your knowledge about the growth of data, knowledge extraction, and the use of models to understand and process large amounts of information in society.
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