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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Intro to OCI AI Services | 20% | - OCI Vision - OCI Language - OCI Document Understanding - OCI Speech |
| Topic 2: Intro to DL Foundations | 15% | - Explain Sequence Models (RNN and LSTM) - Discuss Deep Learning Fundamentals - Explain Convolutional Models (CNN) |
| Topic 3: Intro to AI Foundations | 10% | - Discuss AI Basics - Discuss AI Applications and Types of Data - Explain AI vs ML vs DL |
| Topic 4: Get started with OCI AI Portfolio | 15% | - Explain Responsible AI - Discuss OCI AI Services Overview - Discuss OCI AI Infrastructure Overview - Discuss OCI ML Services Overview |
| Topic 5: OCI Generative AI and Oracle 23ai | 10% | - Discuss Oracle Vector Search - Describe OCI Generative AI Services - Discuss Autonomous Database Select AI |
| Topic 6: Intro to ML Foundations | 15% | - Explain Machine Learning Basics - Discuss Reinforcement Learning Fundamentals - Discuss Unsupervised Learning Fundamentals - Discuss Supervised Learning Fundamentals
|
| Topic 7: Intro to Generative AI and LLMs | 15% | - Discuss Generative AI Overview - Explain Prompt Engineering and Instruction Tuning - Explain Transformers Fundamentals - Explain LLM Fine Tuning - Discuss Large Language Models Fundamentals |
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NEW QUESTION # 42
What are Convolutional Neural Networks (CNNs) primarily used for?
Answer: D
Explanation:
Convolutional Neural Networks (CNNs) are primarily used for image classification and other tasks involving spatial data. CNNs are particularly effective at recognizing patterns in images due to their ability to detect features such as edges, textures, and shapes across multiple layers of convolutional filters. This makes them the model of choice for tasks such as object recognition, image segmentation, and facial recognition.
CNNs are also used in other domains like video analysis and medical image processing, but their primary application remains in image classification.
NEW QUESTION # 43
You are training a logistic regression model to classify emails as spam or not spam. The model is currently classifying too many emails as spam. What would you do to adjust the model?
Answer: A
Explanation:
In binary classification, the decision threshold determines how much predicted probability is required before an observation is assigned to the positive class. Here, spam represents the positive class, and the model is producing too many spam classifications, indicating excessive positive predictions or false positives.
Increasing the classification threshold requires a higher predicted probability before an email is labeled as spam, reducing the number of positive classifications. Oracle Machine Learning documentation defines the probability threshold as the decision point used for binary classification and explains that changing this threshold changes true-positive and false-positive behavior. Oracle Docs Altering individual feature weights, iteration counts, or regularization affects model training rather than directly controlling the classification decision boundary. Therefore, increasing the classification threshold is the most appropriate adjustment.
NEW QUESTION # 44
What feature of OCI Data Science provides an interactive coding environment for building and training models?
Answer: D
Explanation:
In OCI Data Science, Notebook sessions provide an interactive coding environment that is essential for building, training, and deploying machine learning models. These sessions allow data scientists to write and execute code in real time, offering a flexible environment for data exploration, model experimentation, and iterative development. The integration with various OCI services and support for popular machine learning frameworks further enhances the utility of Notebook sessions, making them a crucial tool in the data science workflow.
NEW QUESTION # 45
How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?
Answer: D
Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service facilitates business processes by automating data extraction from documents. This service leverages machine learning to identify, classify, and extract relevant information from various document types, reducing the need for manual data entry and improving efficiency in document processing workflows. Automation of these tasks enables organizations to streamline operations and reduce errors associated with manual data handling.
NEW QUESTION # 46
You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?
Answer: C
Explanation:
For automating transcription tasks in a medical transcription team, the most appropriate OCI AI service to use would be the " Speech " service. This service is designed to convert spoken language into text, which is essential for transcribing spoken medical reports or consultations into written form. The OCI Speech service provides capabilities such as speech-to-text conversion, which is specifically tailored for handling audio input and producing accurate transcriptions.
NEW QUESTION # 47
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