Ultimate AI and Machine Learning Quiz

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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!

34 Questions8 MinutesCreated by LearningApex107

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

Image classification is part of:

Reinforcement Learning

Unsupervised Learning

Supervised Learning

Recommendation Systems 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

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

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

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

Ultimate AI and Machine Learning Quiz

Ultimate AI and Machine Learning Quiz

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