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Certification Path of AWS Certified Machine Learning - Specialty
The Amazon MLS certification path includes only one certification exam.
>> Latest AWS-Certified-Machine-Learning-Specialty Exam Guide <<
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Understanding functional and technical aspects of AWS Certified Machine Learning - Specialty Machine Learning Implementation and Operations
The following will be discussed in AMAZON MLS-C01 exam dumps pdf:
- Recommend and implement the appropriate machine learning services and features for a given problem
- Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance
- Deploy and operationalize machine learning solutions
- Apply basic AWS security practices to machine learning solutions
Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q140-Q145):
NEW QUESTION # 140
A Data Scientist needs to analyze employment dat
a. The dataset contains approximately 10 million
observations on people across 10 different features. During the preliminary analysis, the Data Scientist notices that income and age distributions are not normal. While income levels shows a right skew as expected, with fewer individuals having a higher income, the age distribution also show a right skew, with fewer older individuals participating in the workforce.
Which feature transformations can the Data Scientist apply to fix the incorrectly skewed data? (Choose two.)
- A. One hot encoding
- B. Cross-validation
- C. Numerical value binning
- D. High-degree polynomial transformation
- E. Logarithmic transformation
Answer: B,C
NEW QUESTION # 141
An insurance company is developing a new device for vehicles that uses a camera to observe drivers' behavior and alert them when they appear distracted. The company created approximately 10,000 training images in a controlled environment that a Machine Learning Specialist will use to train and evaluate machine learning models.
During the model evaluation, the Specialist notices that the training error rate diminishes faster as the number of epochs increases and the model is not accurately inferring on the unseen test images.
Which of the following should be used to resolve this issue? (Choose two.)
- A. Add vanishing gradient to the model.
- B. Make the neural network architecture complex.
- C. Perform data augmentation on the training data.
- D. Use gradient checking in the model.
- E. Add L2 regularization to the model.
Answer: C,E
Explanation:
The model must have been overfitted. Regularization helps to solve the overfitting problem in machine learning (as well as data augmentation).
NEW QUESTION # 142
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 recall with respect to the fraudulent class?
- A. Linear support vector machine (SVM)
- B. Single Perceptron with sigmoidal activation function
- C. Naive Bayesian classifier
- D. Decision tree
Answer: C
NEW QUESTION # 143
A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s) Which visualization will accomplish this?
- A. A scatter plot showing the correlation between maximum tree depth and the objective metric.
- B. A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
- C. A scatter plot showing (he performance of the objective metric over each training iteration
- D. A histogram showing whether the most important input feature is Gaussian.
Answer: A
NEW QUESTION # 144
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 recall with respect to the fraudulent class?
- A. Linear support vector machine (SVM)
- B. Single Perceptron with sigmoidal activation function
- C. Naive Bayesian classifier
- D. Decision tree
Answer: C
NEW QUESTION # 145
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