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1. What does ANN stand for?

Explanation: ANN refers to a computational model inspired by the way biological neural networks work.
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Augmented Neural Network

Advanced Neural Network

Artificial Neural Network

Autonomous Neural Network

2. What does API stand for?

Explanation: API allows different software applications to communicate with each other.
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Artificial Processing Interface

Algorithmic Programming Interface

Application Programming Interface

Automated Process Integration

3. What does AUC stand for?

Explanation: AUC measures the performance of a classification model, represented by the area under the ROC curve.
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Area Under Control

Area Under Curve

Algorithmic Uncertainty Control

Analytical Use Case

4. What does AI stand for?

Explanation: AI stands for Artificial Intelligence, which refers to the simulation of human intelligence in machines.
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Artificial Insight

Automated Intelligence

Artificial Intelligence

Augmented Insight

5. What does CRF stand for?

Explanation: CRF is a framework for building probabilistic models to segment and label sequence data.
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Conditional Random Field

Causal Recurrent Filter

Contextual Recursive Field

Constant Random Feature

6. What does CNN stand for in AI?

Explanation: CNN stands for Convolutional Neural Network, a deep learning algorithm primarily used for processing visual data.
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Convolutional Neural Network

Central Neural Node

Conditional Network Node

Convergence Network Node

7. What does DBN stand for?

Explanation: DBN is a generative graphical model consisting of multiple layers of hidden units, used for unsupervised learning.
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Deep Boltzmann Network

Distributed Boltzmann Network

Deep Belief Network

Dense Belief Network

8. What does DNN stand for?

Explanation: DNN refers to a neural network with multiple hidden layers between the input and output layers.
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Dense Neural Network

Distributed Neural Network

Deep Neural Network

Dual Node Network

9. What does XGBoost stand for?

Explanation: XGBoost is an optimized distributed gradient boosting library designed to be highly efficient and flexible for supervised learning tasks.
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Extreme Gradient Boosting

Extended Gradient Boosting

Exponential Gradient Boost

Extra General Boosting

10. What does FNN stand for?

Explanation: FNN refers to a type of neural network where connections between nodes do not form a cycle.
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Fully Neural Network

Feedforward Neural Network

Frequent Neural Network

Fractional Neural Network

11. What does GAN stand for?

Explanation: GAN refers to Generative Adversarial Network, a model where two neural networks compete to generate new, synthetic data that is similar to real data.
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General Adversarial Network

Generative Adversarial Network

Gradient Advancement Network

Global Adaptation Network

12. What does GPU stand for?

Explanation: GPU refers to a specialized processor designed to accelerate graphics rendering and computational tasks, widely used in training AI models.
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General Processing Unit

Graphical Processing Unit

Gradient Processing Unit

Global Processing Unit

13. What does IoT stand for?

Explanation: IoT refers to the network of physical devices that are connected and able to exchange data.
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Interface of Technology

Internet of Things

Information of Technology

Integrated Operational Technology

14. What does KNN stand for?

Explanation: KNN is a simple, instance-based learning algorithm used for classification and regression.
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K-Nearest Neighbors

Knowledge Neural Network

Key Neural Node

Kinetic Neural Network

15. What does LLM stand for in the context of AI and ML?

Explanation: A Large Language Model (LLM) is an AI model trained on vast amounts of text data to understand and generate human-like language.
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Low-Level Modeling

Large Language Model

Logical Learning Machine

Long-Latency Memory

16. What does LSTM stand for?

Explanation: LSTM is a type of RNN designed to learn long-term dependencies in sequence data.
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Long Short-Term Memory

Linear Statistical Time Model

Large Scalable Time Module

Learned Sequential Timing Mechanism

17. What does MLOps stand for?

Explanation: MLOps is a practice that combines machine learning and DevOps to streamline the process of building, deploying, and maintaining machine learning models.
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Machine Learning Options

Machine Learning Operations

Model Learning Optimization

Modular Learning Operations

18. What does ML stand for?

Explanation: ML refers to Machine Learning, a branch of AI that allows systems to learn from data without being explicitly programmed.
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Machine Learning

Model Learning

Metric Learning

Module Logic

19. What does MLP stand for?

Explanation: MLP refers to a class of feedforward artificial neural networks with multiple layers of nodes.
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Multi-Layer Perception

Multi-Layer Processing

Multi-Layer Perceptron

Maximum Likelihood Processing

20. What does NLP stand for?

Explanation: NLP refers to Natural Language Processing, a field of AI focused on the interaction between computers and human language.
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Neural Learning Protocol

Natural Language Processing

Nominal Language Prediction

Numeric Learning Process

21. What does PCA stand for?

Explanation: PCA is a dimensionality-reduction technique used to reduce the complexity of large datasets while retaining most of the variance.
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Principal Component Analysis

Process Control Algorithm

Primary Computing Algorithm

Predictive Component Analysis

22. What does ROC stand for?

Explanation: ROC is a graphical plot used to assess the diagnostic ability of binary classifiers.
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Rate of Change

Random Output Classification

Receiver Operating Characteristic

Recursive Output Calculation

23. What does RAG stand for in AI development?

Explanation: RAG is stands for Retrieval-Augmented Generation. It helps AI look up real info before answering, so the reply is more accurate.
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Randomized Attention Generator

Recursive Analytical Graph

Resource Allocation Grid

Retrieval-Augmented Generation

24. What does RNN stand for?

Explanation: RNN stands for Recurrent Neural Network, a class of neural networks that is used for processing sequences of data.
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Recurrent Neural Network

Regular Neural Network

Recursive Neural Node

Randomized Neural Network

25. What does RL stand for?

Explanation: RL stands for Reinforcement Learning, a type of machine learning where an agent learns to make decisions by interacting with its environment.
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Recurrent Learning

Reinforcement Learning

Recursive Learning

Rational Learning

26. What does RLHF stand for?

Explanation: RLHF is a method in which a human provides feedback on an agent's behavior to improve its learning process.
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Real-time Learning of Hyperparameter Fine-tuning

Reinforcement Learning with Human Feedback

Recursive Learning in High Frequency

Rational Learning with Hybrid Framework

27. What does RPA stand for?

Explanation: RPA refers to the technology used for automating routine tasks using software robots or bots.
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Repetitive Processing Algorithm

Robotic Process Automation

Real-time Process Analysis

Recursive Path Algorithm

28. What does SGD stand for?

Explanation: SGD is an optimization algorithm used to minimize the error in machine learning models.
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Stochastic Gradient Descent

Statistical Gradient Descent

Sequential Gradient Descent

Supervised Gradient Descent

29. What does SVM stand for?

Explanation: SVM is a supervised machine learning model used for classification and regression analysis.
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Support Vector Machine

Supervised Vector Model

Signal Validation Model

Statistical Variance Model

30. What does TPU stand for?

Explanation: TPU is a custom-developed application-specific integrated circuit (ASI , used to accelerate machine learning workloads, specifically designed by Google for TensorFlow.
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Tensor Processing Unit

Transfer Processing Unit

Time-based Processing Unit

Threaded Processing Unit

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