Which practice ensures ML models are continuously monitored in production?
- CI/CD
- Model Drift Detection
- A/B Testing
- All of these
Answer: All of these
MLOps combines CI/CD, drift detection, A/B testing for production ML.
GK Questions
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The technique that enables LLMs to execute code is called ________ Calling.
- Function
- Ka
- -a
- AI-based / Machine Learning
Answer: Function
Function calling enables LLMs to invoke APIs, run code, query databases.
Parameter-Efficient Fine-Tuning reduces compute costs for adapting large models.
- True
- False
Answer: True
PEFT methods update small subset of parameters, reducing compute/memory.
Which method reduces LLM hallucinations by grounding responses in external knowledge?
- Fine-tuning
- RAG
- Prompt Engineering
- All of these
Answer: RAG
Retrieval-Augmented Generation combines LLMs with external knowledge retrieval.
The technique that enables LLMs to reason step-by-step is called Chain-of-________.
- Thought
- Serverless
- Board
- Academic Bank of Credits / DigiLocker
Answer: Thought
Chain-of-Thought prompting encourages LLMs to generate reasoning steps.
The technique that groups similar data points without labels is called ________.
- Deployment
- DID / Decentralized Identifiers
- Thought
- Clustering
Answer: Clustering
Clustering discovers natural groupings in unlabeled data.
Feature engineering creates new input variables to improve model performance.
- True
- False
Answer: True
Feature engineering: domain knowledge, transformations, interactions, encoding.
Which technique enables prediction of future values based on historical data?
- Regression
- Classification
- Time Series Forecasting
- Clustering
Answer: Time Series Forecasting
Time series forecasting models temporal patterns for demand prediction, anomaly detection.
The technology that enables querying data in object storage is called ________ Query.
- Serverless
- Forum / Index
- Parameter
- Kubernetes
Answer: Serverless
Serverless query engines enable SQL queries on object storage using schema-on-read.
Data lakes store raw data while data warehouses store structured data.
- True
- False
Answer: True
Data lakes store raw structured/unstructured data; warehouses store curated data.
Which storage format is optimized for analytics workloads?
- CSV
- JSON
- Parquet
- Avro
Answer: Parquet
Parquet is columnar storage format optimized for analytics: compression, predicate pushdown.
The pattern of processing data as it arrives is called ________ Processing.
- Inversion
- Stream
- Reinforcement
- Application-Layer
Answer: Stream
Stream processing handles continuous data flows for real-time insights.
Change Data Capture enables real-time replication of database changes.
- True
- False
Answer: True
CDC captures database operations and streams to targets for real-time analytics.
Indicators of Compromise include malicious IPs, domains, and file hashes.
- True
- False
Answer: True
IOCs are forensic artifacts indicating potential breaches. Used for proactive blocking.
Network segmentation limits blast radius of security incidents in Zero Trust.
- True
- False
Answer: True
Micro-segmentation creates granular security zones, containing breaches and limiting attacker movement.
Which technology enables continuous verification of user identity in Zero Trust?
- Multi-Factor Authentication
- Adaptive Authentication
- Both A and B
- Neither
Answer: Both A and B
MFA requires multiple authentication factors; adaptive authentication adjusts requirements based on risk context.
The Indian government's initiative for promoting electric vehicle adoption is called ________ India.
- FAME
- ONDC
- NAT
- L
Answer: FAME
FAME provides demand incentives for EVs and charging infrastructure.
The technique that enables efficient training of large models by partitioning across devices is called ________ Parallelism.
- Kubernetes
- Ethical / CEH
- Model / Pipeline
- Transaction / AML
Answer: Model / Pipeline
Model parallelism splits model layers across devices; pipeline parallelism stages computation. Critical for scaling LLM training.
Positional encodings enable Transformers to understand token order in sequences.
- True
- False
Answer: True
Positional encodings add sequence order information to token embeddings, critical for language understanding tasks.
Which component enables Transformers to focus on relevant parts of input sequences?
- Attention Mechanism
- Feed-Forward Networks
- Positional Encoding
- Layer Normalization
Answer: Attention Mechanism
Self-attention computes weighted relationships between tokens, enabling context-aware processing. Foundation of Transformer success.