A logistics company needs a forecast model to predict next month's inventory requirements for a single item in 10 warehouses. A machine learning specialist uses Amazon Forecast to develop a forecast model from 3 years of monthly data. There is no missing data. The specialist selects the DeepAR+ algorithm to train a predictor. The predictor means absolute percentage error (MAPE) is much larger than the MAPE produced by the current human forecasters.
Which changes to the CreatePredictor API call could improve the MAPE? (Choose two.)

1. A. Set PerformAutoML to true.
2. B. Set ForecastHorizon to 4.
3. C. Set ForecastFrequency to W for weekly.
4. D. Set PerformHPO to true.
5. E. Set FeaturizationMethodName to filling.

Correct Answer: CD

A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions
Here is an example from the dataset
"The quck BROWN FOX jumps over the lazy dog "
Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Select THREE)

1. A. Perform part-of-speech tagging and keep the action verb and the nouns only
2. B. Normalize all words by making the sentence lowercase
3. C. Remove stop words using an English stopword dictionary.
4. D. Correct the typography on "quck" to "quick."
5. E. One-hot encode all words in the sentence
6. F. Tokenize the sentence into words.

Correct Answer: BCF

A health care company is planning to use neural networks to classify their X-ray images into normal and abnormal classes. The labeled data is divided into a training set of 1,000 images and a test set of 200 images. The initial training of a neural network model with 50 hidden layers yielded 99% accuracy on the training set, but only 55% accuracy on the test set.
What changes should the Specialist consider to solve this issue? (Choose three.)

1. A. Choose a higher number of layers
2. B. Choose a lower number of layers
3. C. Choose a smaller learning rate
4. D. Enable dropout
5. E. Include all the images from the test set in the training set
6. F. Enable early stopping

Correct Answer: ADE

A Machine Learning Specialist is working for a credit card processing company and receives an unbalanced dataset containing credit card transactions. It contains 99,000 valid transactions and 1,000 fraudulent transactions The Specialist is asked to score a model that was run against the dataset The Specialist has been advised that identifying valid transactions is equally as important as identifying fraudulent transactions
What metric is BEST suited to score the model?

1. A. Precision
2. B. Recall
3. C. Area Under the ROC Curve (AUC)
4. D. Root Mean Square Error (RMSE)

Correct Answer: A

A media company with a very large archive of unlabeled images, text, audio, and video footage wishes to index its assets to allow rapid identification of relevant content by the Research team. The company wants to use machine learning to accelerate the efforts of its in-house researchers who have limited machine learning expertise.
Which is the FASTEST route to index the assets?

1. A. Use Amazon Rekognition, Amazon Comprehend, and Amazon Transcribe to tag data into distinct categories/classes.
2. B. Create a set of Amazon Mechanical Turk Human Intelligence Tasks to label all footage.
3. C. Use Amazon Transcribe to convert speech to tex
4. D. Use the Amazon SageMaker Neural Topic Model (NTM) and Object Detection algorithms to tag data into distinct categories/classes.
5. E. Use the AWS Deep Learning AMI and Amazon EC2 GPU instances to create custom models for audio transcription and topic modeling, and use object detection to tag data into distinct categories/classes.

Correct Answer: A