AI terms #4 practice 2

Froggy Jumps

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Choose the correct option for each question

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Coach Ana María

Colombia

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AI terms #4 practice 2


Froggy Jumps AI terms #4 practice 2Version en ligne Choose the correct option for each question par Coach Ana María 1 What is the main goal of data preprocessing? a Visualizing data b Preparing raw data for modeling c Deploying a model 2 Data cleaning removes: a Useful patterns b System logs c Errors and duplicates 3 Data normalization is mainly used to: a Encrypt the dataset b Match numeric features to a common scale c Group data by category 4 Data labeling is required in: a Supervised learning b Unsupervised learning c Reinforcement learning only 5 Data augmentation helps prevent: a Overfitting b Tokenization c Parallelism 6 ETL stands for: a Evaluate, Train, Load b Extract, Transform, Load c Encode, Transfer, Label 7 A data pipeline is: a A data storage format b An encryption method c A sequence of automated data steps 8 Batch processing analyzes data: a Every microsecond b In large groups at scheduled times c Only in real time 9 Real-time processing is ideal for: a Monthly reports b Security alerts c Data warehousing 10 A vector database stores: a CSV files b Text documents c Numerical embeddings 11 An embedding index helps with: a Data encryption b Fast similarity search c Version control 12 RAG combines retrieval with: a Encryption b Data compression c Generative models 13 Similarity search finds items based on: a File size b Semantic distance between vectors c 14 True or false: Data cleaning happens after model training. a True b False c 15 True or False: A vector database can replace a relational database in all use cases. a True b False c 16 True or false: RAG helps reduce model hallucinations. a True b False c 17 Fill in the blank: Data __________ generates synthetic samples to expand a dataset. a Augmentation b Cleaning c Labeling 18 Fill in the blank: ETL stands for Extract, Transform, _______. a Normalization b Load c Cleaning 19 Which process scales numeric data? a Labeling b Augmentation c Normalization 20 Vector databases are essential for: a Semantic search and RAG b Deleting corrupted data c Storing SQL tables only

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AI terms #4 practice 2

Froggy Jumps

À propos de cette activité

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Téléchargez la version pour jouer sur papier

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Froggy Jumps

AI terms #4 practice 2Version en ligne

par Coach Ana María

What is the main goal of data preprocessing?

Data cleaning removes:

Data normalization is mainly used to:

Data labeling is required in:

Data augmentation helps prevent:

ETL stands for:

A data pipeline is:

Batch processing analyzes data:

Real-time processing is ideal for:

A vector database stores:

An embedding index helps with:

RAG combines retrieval with:

Similarity search finds items based on:

True or false: Data cleaning happens after model training.

True or False: A vector database can replace a relational database in all use cases.

True or false: RAG helps reduce model hallucinations.

Fill in the blank: Data __________ generates synthetic samples to expand a dataset.

Fill in the blank: ETL stands for Extract, Transform, _______.

Which process scales numeric data?

Vector databases are essential for: