Free AWS-Certified-Machine-Learning-Specialty Exam Braindumps

A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.

Based on this information which model would have the HIGHEST accuracy?

1. A. Long short-term memory (LSTM) model with scaled exponential linear unit (SELL))
2. B. Logistic regression
3. C. Support vector machine (SVM) with non-linear kernel
4. D. Single perceptron with tanh activation function

Correct Answer: C

A Machine Learning Specialist is attempting to build a linear regression model.
Given the displayed residual plot only, what is the MOST likely problem with the model?

1. A. Linear regression is inappropriat
2. B. The residuals do not have constant variance.
3. C. Linear regression is inappropriat
4. D. The underlying data has outliers.
5. E. Linear regression is appropriat
6. F. The residuals have a zero mean.
7. G. Linear regression is appropriat
8. H. The residuals have constant variance.

Correct Answer: D

Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3
The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3
Which approach will provide the information required for further analysis?

1. A. Use Amazon Comprehend with the transcribed files to build the key topics
2. B. Use Amazon Translate with the transcribed files to train and build a model for the key topics
3. C. Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics
4. D. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics

Correct Answer: B

A gaming company has launched an online game where people can start playing for free but they need to pay if they choose to use certain features The company needs to build an automated system to predict whether or not a new user will become a paid user within 1 year The company has gathered a labeled dataset from 1 million users
The training dataset consists of 1.000 positive samples (from users who ended up paying within 1 year) and 999.1 negative samples (from users who did not use any paid features) Each data sample consists of 200 features including user age, device, location, and play patterns
Using this dataset for training, the Data Science team trained a random forest model that converged with over 99

1. A. Add more deep trees to the random forest to enable the model to learn more features.
2. B. indicate a copy of the samples in the test database in the training dataset
3. C. Generate more positive samples by duplicating the positive samples and adding a small amount of noise to the duplicated data.
4. D. Change the cost function so that false negatives have a higher impact on the cost value than false positives
5. E. Change the cost function so that false positives have a higher impact on the cost value than false negatives

Correct Answer: CD

During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates What is the MOST likely cause of this issue?

1. A. The class distribution in the dataset is imbalanced
2. B. Dataset shuffling is disabled
3. C. The batch size is too big
4. D. The learning rate is very high

Correct Answer: B