Oracle
1Z0-1122-24
Oracle Cloud Infrastructure 2024 AI Foundations Associate
QUESTION & ANSWERS
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QUESTION: 1
Which algorithm is primarily used for adjusting the weights of connections between neurons during the
training of an Artificial Neural Network (ANN)?
Option A : Gradient Descent
Option B : Backpropagation
Option C : Random Forest
Option D : Support Vector Machine
Correct Answer: B
Explanation/Reference:
Backpropagation is the algorithm primarily used for adjusting the weights of connections between neurons during the training
of an Artificial Neural Network (ANN). It is a supervised learning algorithm that calculates the gradient of the loss function with
respect to each weight by applying the chain rule, propagating the error backward from the output layer to the input layer. This
process updates the weights to minimize the error, thus improving the model's accuracy over time. Gradient Descentis closely
related as it is the optimization algorithm used to adjust the weights based on the gradients computed by backpropagation, but
backpropagation is the specific method used to calculate these gradients.
QUESTION: 2
Which Deep Learning model is well-suited for processing sequential data, such as sentences?
Option A : Generative Adversarial Network (GAN)
Option B : VariationalAutoencoder(VAE)
Option C : Recurrent Neural Network (RNN)
Option D : Convolutional Neural Network (CNN)
Correct Answer: C
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Explanation/Reference:
Recurrent Neural Networks (RNNs) are a type of deep learning algorithm that can process sequential data, such as sentences,
speech, or time series. They are composed of recurrent units that have a loop that allows them to store information from
previous inputs and pass it to the next inputs. This way, they can capture the temporal dependencies and context within a
sequence. RNNs can be used for various natural language processing tasks, such as text generation, machine translation,
sentiment analysis, speech recognition, etc. However, RNNs also suffer from some limitations, such as vanishing or exploding
gradients, difficulty in modeling long-term dependencies, and high computational cost. Therefore, some variants and
extensions of RNNs have been proposed to overcome these challenges, such as Long Short-Term Memory (LSTM), Gated
Recurrent Unit (GRU), Bidirectional RNN (BiRNN), Attention Mechanism, etc. References: : [Recurrent neural network -
Wikipedia], [What are Recurrent Neural Networks? | IBM], [Recurrent Neural Network (RNN) in Machine Learning]
QUESTION: 3
Which feature of OCI Speech helps make transcriptions easier to read and understand?
Option A : Audio tuning
Option B : Timestamping
Option C : Profanity filtering
Option D : Text normalization
Correct Answer: D
Explanation/Reference:
The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken
language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation,
and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization
enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications. Top
of Form Bottom of Form
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QUESTION: 4
What can Oracle Cloud Infrastructure Document Understanding NOT do?
Option A : Generate transcript from documents
Option B : Extract tables from documents
Option C : Classify documents into different types
Option D : Extract text from documents
Correct Answer: A
Explanation/Reference:
Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables,
classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically
refers to converting spoken language into written text, which is a function associated with speech-to-text services, not
document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document
Understanding is designed to do .
QUESTION: 5
Which feature is NOT available as part of OCI Speech capabilities?
Option A : Uses extensive data science experience to operate
Option B : Provides timestamped, grammatically accurate transcriptions
Option C : Transcribes audio and video files into text
Option D : Supports multiple languages including English, Spanish, and Portuguese
Correct Answer: A
Explanation/Reference:
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OCI Speech capabilities are designed to be user-friendly and do not require extensive data science experience to operate. The
service provides features such as transcribing audio and video files into text, offering grammatically accurate transcriptions,
supporting multiple languages, and providing timestamped outputs. These capabilities are built to be accessible to a broad
range of users, making speech-to-text conversion seamless and straightforward without the need for deep technical expertise.
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