What is the hardware component designed to process many tasks simultaneously, ideal for image processing and model training? Field-programmable gate array (FPGA) Tensor processing unit (TPU) Graphical processing unit (GPU) Central processing unit (CPU)

Graphical processing unit (GPU)

Comprehensive Guide to Machine Learning Concepts and Techniques

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Computer Science - Software Engineering

user_kumartyv Created by 7 mon ago

Cards in this deck(34)

What is a large collection of data used to train and test machine learning models, often normalized and sometimes labeled?

Which type of machine learning involves models with many layers of artificial neurons to learn patterns from large datasets?

What is the hardware component designed to process many tasks simultaneously, ideal for image processing and model training?

What is the process of adjusting and optimizing a neural network's hyperparameters to improve its performance?

What type of model is specifically designed to understand and generate human language, trained on vast amounts of text data?

What term describes the time or delay for a model to return an output after receiving an input?

What is the function that quantifies how far a model's predictions are from the actual values, guiding model improvement?

In an LSTM network, what stores important information over time?

What is the term for systematically prejudiced error in a model's predictions due to erroneous assumptions during learning?

What is the tendency in model training to focus on data or outcomes that support existing assumptions, ignoring contradictory evidence?

What type of bias originates from historical data reflecting past prejudices, leading to biased predictions?

What occurs when the labels assigned to training data are inconsistent or subjective, misleading model learning?

What type of bias arises from the language used in training data, affecting model interpretation and generation?

What occurs when training data is not representative of the overall population, leading to poor model performance on unseen data?

What type of bias is introduced when the data selection process favors certain outcomes, impacting model validity?

What is the process of converting raw data into a format suitable for model use, involving cleaning and normalizing?

What type of neural network takes sequential data as input and learns by remembering previous information in the sequence?

What method is used to train RNNs by unrolling the network over time to learn from sequences of data?

What is the method of representing text data by counting word occurrences, ignoring word order?

What type of RNN is designed to remember information for long periods, addressing the vanishing gradient problem?

What process in neural networks allows models to weigh the importance of different input data for predictions?

What is artificially generated data that mimics real-world data, often used to supplement training data?

What is the special hardware designed by Google to speed up machine learning tasks, especially for deep learning?

What type of neural network uses self-attention to process data efficiently, especially for language tasks?

What problem occurs when training deep neural networks, where gradients become extremely small or 'vanish'?

What are the values that a neural network adjusts during training to improve its predictions, controlling the signal strength between neurons?

What parameters in neural networks allow the model to fit data better by shifting the activation function?

What field of machine learning focuses on teaching computers to understand and respond to human language?

What subset of NLP deals with machine reading comprehension and understanding human language?

What process connects the meaning of different parts of a text to maintain overall context?

What is the process of breaking down text into individual words (tokens) for processing?

What analysis involves understanding language in its context, such as recognizing sarcasm or implied meanings?

What analysis involves figuring out the meaning of words and sentences in a text?

What analysis involves understanding the structure of sentences to comprehend grammar and sentence patterns?

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Comprehensive Guide to Machine Learning Concepts and Techniques

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