Ultimate AI and Machine Learning Quiz
Ultimate AI and Machine Learning Quiz
Test your knowledge with our comprehensive quiz on Artificial Intelligence and Machine Learning! Dive into various topics ranging from basic concepts to intricate algorithms and applications.
- Multiple choice and checkbox questions
- Evaluate your understanding with real-world applications
- Perfect for students and professionals alike!
In the input feature space the points are representable as a vector of real numbers
True
False
"If our brain is collecting elements, the interpretation is to let them appear as simple as possible", this concept comes from
Bratton's stack
Law of Pragnanz
Bertin's Theory
Occam's Razor
Choose the right option about the size of Machine Learning, Deep Learning and Artificial Intelligence.
ML > DL > AI
DL > ML > AI
AI > DL > ML
AI > ML > DL
What type of learning is based on a reward / penalty?
Supervised Learning
Unsupervised Learning
Eager Learning
Reinforcement Learning
The success and the explosion of AI success is mainly related to
Rising of big data
Improved models and algorithms to create large neural networks
The capability to crunch the data with GPUs
The designer's brain
All of the above
None of the above
Image classification is part of:
Reinforcement Learning
Unsupervised Learning
Supervised Learning
Recommendation Systems are part of:
Reinforcement Learning
Unsupervised Learning
Supervised Learning
Forecasting are part of:
Reinforcement Learning
Unsupervised Learning
Supervised Learning
Real-time decisions are part of:
Reinforcement Learning
Unsupervised Learning
Supervised Learning
Big data visualization are part of:
Reinforcement Learning
Unsupervised Learning
Supervised Learning
CL: Clusterization, C: Classification, R: Regression, SL: Supervised Learning, UL: Unsupervised Learning, choose the correct association:
CL -> SL, C -> UL, R -> SL
CL -> UL, C -> SL, R -> UL
CL -> UL, C -> SL, R -> SL
CL -> UL, C -> UL, R -> SL
The "desired output" is a concept which makes sense in:
Reinforcement Learning
Supervised Learning
Unsupervised Learning
Choose the 2 right answers about inductive and deductive learning:
Inductive: works from theory to observation and looks for confirmation
Deductive: works from theory to observation and looks for confirmation
Inductive: works from specific observations to broad theory and general conclusions
Deductive: works from specific observations to broad theory and general conclusions
Indicate the most frequently used approach:
Inductive
Deductive
Choose the best answer: what are the 3 main components of every ML algorithm?
Training set, Test set, Validation Set
Representation, Evaluation, Optimization
Speed, Accuracy, Interoperability
Portability, Scalability, Explainability
In which era are we living, nowadays?
Collaborative Economy Age
Social Media Age
Autonomous World Age
Internet Era
It is always better to keep the order of the 5 steps of ML workflow
True
False
Choose the configuration which better describes the layers from data centers towards devices
Fog, Cloud, Edge
Edge, Cloud, Fog
Fog, Edge, Cloud
Cloud, Fog, Edge
Passive data is:
Data of passive events perceived by sensors which can communicate also each other
Data perceived by sensors that don't actively communicate
Data which sensor receive passively from the other ones
Data of sensors with no battery on board
Active data is:
Data perceived by sensor that actively do sensing
Data of events which actively trigger sensors
Data perceived by sensor which actively communicate through streams
Data of sensors with battery on board
Dynamic data is:
Data perceived by sensors with battery on board
Hybrid solution between passive and active data
Data perceived by sensors that communicate with IoT applications
What are the 3 categories of IoT based on the usage of clients?
Personal IoT, Global IoT, Companies IoT
Private IoT, Public IoT, Internet IoT
Consumer IoT, Commercial IoT, Industrial IoT
Digital IoT, Collaborative IoT, Autonomous IoT
Pirello Connesso is a good example of usage of:
Passive Data
Dynamic Data
Active Data
Smart speakers are a good example of usage of
Dynamic Data
AIoT
All of the above
Choose the correct order of complexity concerning the types of analytics:
Descriptive, Prescriptive, Predictive, Diagnostic
Diagnostic, Descriptive, Predictive, Prescriptive
Diagnostic, Predictive, Descriptive, Prescriptive
Descriptive, Diagnostic, Predictive, Prescriptive
In the step 2 of ML workflow you may deal with unstructured or heterogeneous data, this is called
Data leakage
Data preprocessing
Data preparation
Data wrangling
In the step 2 of ML workflow you may convert the raw data into a clean data set, this is called
Data leakage
Data preprocessing
Data preparation
Data wrangling
The problem of using data from test set to train the model is called
Overfitting
Underfitting
Data leakage
A solution to avoid data leakage is
Reduce the dataset
Control DoF
Control #Par
Partition Training and Test sets
Indicate the correct answer:
P=1 Manhattan Distance, p=2 Euclidean Distance, p->inf Chebyshev Distance
P=1 Manhattan Distance, p=2 Chebyshev Distance, p->inf Euclidean Distance
P=1 Euclidean Distance, p=2 Manhattan Distance, p->inf Chebyshev Distance
P=1 Chebyshev Distance, p=2 Euclidean Distance, p->inf Manhattan Distance
SIFT and SURF algorithms belong to the family of:
Histogram
Key Point Matching
Image Hash
You want to choose the more suitable solution for rotations:
SIFT
SURF
You want to choose the more suitable solution for scaling:
SIFT
SURF
You want to choose the more suitable solution for speed:
SIFT
SURF
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