Additional Terminology Flashcards

1
Q

What is Backpropagation Through Time (BPTT)?

A

A method to train recurrent neural networks by unfolding them in time.

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2
Q

What is the Bag-of-Words model in NLP?

A

A representation of text that disregards grammar and word order but keeps word frequency.

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3
Q

What are biases in machine learning?

A

Systematic errors introduced in models due to assumptions in data or algorithms.

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4
Q

What is selection bias in datasets?

A

A bias introduced when the sample is not representative of the population.

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5
Q

What is confirmation bias in data interpretation?

A

The tendency to favor information that confirms one’s preconceptions.

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6
Q

What is historical bias in datasets?

A

Bias introduced due to outdated or non-representative historical data.

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7
Q

What is labelling bias in datasets?

A

Incorrect or inconsistent data labeling that affects model performance.

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8
Q

What is linguistic bias in datasets?

A

A bias that occurs when certain linguistic groups are favored over others in data.

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9
Q

What is sampling bias in datasets?

A

Bias caused by a non-random selection of data samples.

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10
Q

What is the role of a dataset in machine learning?

A

A collection of data used to train and evaluate machine learning models.

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11
Q

What is deep learning?

A

A subset of machine learning using neural networks with many layers.

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12
Q

What is a graphical processing unit (GPU) in deep learning?

A

A hardware unit that accelerates the computation of deep learning models.

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13
Q

What is hyperparameter tuning in machine learning?

A

The process of adjusting model settings to optimize performance.

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14
Q

What is a large language model (LLM)?

A

A neural network model trained on massive amounts of text data for language tasks.

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15
Q

What is latency in computing?

A

The delay before a transfer of data begins following an instruction.

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16
Q

What is long short-term memory (LSTM)?

A

A type of recurrent neural network that can learn long-term dependencies.

17
Q

What is a loss function in machine learning?

A

A function that measures the difference between the predicted and actual outputs.

18
Q

What is the memory cell state in LSTM?

A

The internal state of the LSTM that stores information across time steps.

19
Q

What is natural language processing (NLP)?

A

A field of AI focused on the interaction between computers and human language.

20
Q

What is discourse integration in NLP?

A

The process of linking sentences together in a coherent text.

21
Q

What is lexical analysis in NLP?

A

The process of breaking text into tokens, such as words or phrases.

22
Q

What is pragmatic analysis in NLP?

A

Understanding the intended meaning of words in context, beyond literal meaning.

23
Q

What is semantic analysis in NLP?

A

The process of understanding the meaning of words and sentences.

24
Q

What is syntactical analysis (parsing) in NLP?

A

The process of analyzing sentence structure to understand grammar.

25
Q

What is natural language understanding (NLU)?

A

A subset of NLP that focuses on machine comprehension of text meaning.

26
Q

What is pre-processing in machine learning?

A

Data preparation steps like cleaning and transforming before model training.

27
Q

What is a recurrent neural network (RNN)?

A

A neural network model that processes sequential data by maintaining a memory of past inputs.

28
Q

What is the self-attention mechanism?

A

A method used in transformers to focus on different parts of the input sequence for better context understanding.

29
Q

What is synthetic data?

A

Data artificially generated rather than obtained by direct measurement.

30
Q

What is a tensor processing unit (TPU)?

A

A hardware accelerator designed by Google for efficient deep learning computation.

31
Q

What is a transformer neural network (transformer NN)?

A

A model architecture designed to handle sequential data using self-attention mechanisms.

32
Q

What is the vanishing gradient problem?

A

A problem where gradients diminish during backpropagation, making it difficult to train deep neural networks.

33
Q

What are weights in neural networks?

A

The parameters in the network that are adjusted during training to minimize the loss.