For this question, refer to the Helicopter Racing League (HRL) case study. HRL wants better prediction accuracy from their ML prediction models. They want you to use Google's AI Platform so HRL can understand and interpret the predictions. What should you do?
To enhance prediction accuracy and allow understanding and interpretation of machine learning model predictions, you should use Explainable AI. Explainable AI provides insights into how a model's predictions are made by explaining the impact of each feature on the prediction. This helps in verifying model behavior, recognizing bias, and improving model performance. Using Explainable AI aligns with HRL's requirement to understand and interpret predictions, thereby facilitating better decision-making.
Answer A AI Explanations helps you understand your model's outputs for classification and regression tasks. Whenever you request a prediction on AI Platform, AI Explanations tells you how much each feature in the data contributed to the predicted result. You can then use this information to verify that the model is behaving as expected, recognize bias in your models, and get ideas for ways to improve your model and your training data. https://cloud.google.com/ai-platform/prediction/docs/ai-explanations/overview
Got this question in my exam, answered A
It's now Vertex AI
Answer is A
vote A
The correct answer is A: Use Explainable AI. To understand and interpret the predictions made by HRL's ML prediction models, you should use Explainable AI. Explainable AI, also known as XAI, is a suite of tools and techniques that helps you understand and interpret the predictions made by machine learning models. With Explainable AI, you can get insights into how the model made a particular prediction, which can help you understand the underlying factors that influenced the prediction. This can help HRL improve the accuracy of their predictions and make more informed decisions based on the output of their models. Option B: Vision AI is a suite of tools and services that helps you build and deploy computer vision applications. It is not relevant to understanding and interpreting the predictions made by HRL's ML prediction models.
Option C: Google Cloud's operations suite is a set of tools and services that helps you monitor, troubleshoot, and optimize your Google Cloud resources. It is not relevant to understanding and interpreting the predictions made by HRL's ML prediction models. Option D: Jupyter Notebooks is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is not relevant to understanding and interpreting the predictions made by HRL's ML prediction models.
Explainable AI now included with Vertex AI https://cloud.google.com/explainable-ai
Answer A is almost correct ;). Not it should be Vertex AI.
A. Use Explainable AI.
Had this quection on my exam.
Answer is A. https://cloud.google.com/explainable-ai
https://cloud.google.com/aiplatform/prediction/docs/ai-explanations/overview
Option A - Now its Vertex AI
hey guys new Qs posted as of July 12th, 2021, All 21 new Qs in Question #152
A is the correct answer
A is Correct
A is ok
Answer A, BUT: "This legacy version of AI Platform Prediction is deprecated and will no longer be available on Google Cloud after January 31, 2025. All models, associated metadata, and deployments will be deleted after January 31, 2025. Migrate your resources to Vertex AI to get new machine learning features that are unavailable in AI Platform."