Amazon MLA-C01 Dumps
| Exam Code | MLA-C01 |
| Exam Name | Certified Machine Learning Engineer - Associate |
| Update Date | 05 Oct, 2024 |
| Total Questions | 675 Questions Answers With Explanation |
$499
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Question # 1
A college endowment office is using S3 data lake with structured and unstructured data to identify potential big donors. Many different data lake records refer to the same person, so fundraisers need to de-duplicate data before storing it and preparing for further processing. What is the easiest and most effective way to achieve that goal?
A Write a Python code for a custom de-duplication and run it on EMR cluster.
B Use AWS Glue Crawler to identify and eliminate duplicate people.
C Find a matching algorithm on AMI Marketplace.
D Store data in compressed JSON format.
Question # 2
A Machine Learning Engineer is tasked with developing a server less BI Dashboard on AWS that has ML methods build-in. What is the best AWS service he can choose?
A Google BI integrated with AWS Dash
B AWS Quick Sight
C AWS Tableau
D Sage Maker Server less
Question # 3
Mark is running a small print-on-demand (POD) business. This month he has been selling an average of 5 T-shirts per day. He is running low on inventory and he wants to calculate the probability that he will sell more than 10 T-shirts tomorrow. What probability distribution should he use for that calculation?
A Poisson distribution
B Normal (Gaussian) distribution
C Modified alpha distribution
D Student t-distribution
Question # 4
The AWS Glue Data Catalog contains references to data that are used as sources and targets of extract, transform, and load (ETL) jobs in AWS Glue. To create a data warehouse or data lake, a user must catalog this data. One way to take inventory of the data in the data store is to run a Glue crawler. What is NOT the datastore a crawler can connect to?
A Amazon S3
B Amazon Redshift
C JDBC API
D Amazon Elasti Cache
Question # 5
A Data Scientist is dealing with s binary classification problem with highly imbalanced classes in a 1:200 ratio. He wants to fit and evaluate a decision tree algorithm but does not expect it to perform very well on a raw unbalanced dataset. What are the two techniques he can use as data preparation? (Select TWO.)
A Transform Training Data with SMOTE
B Under-sample majority (normal) class.
C Use SVM (Support-Vector Machine) Algorithm.
D Normalize features of the majority class.
E Collect more data.
Question # 6
A researcher in a hospital is building an ML model that ingests the dataset containing patients’ names, ages, medical record numbers, medical conditions, medications dosages and strengths, doctors’ notes, and other protected health information (PHI). The dataset will be stored on Amazon S3. What is the BEST way to securely store that data?
A Redact patients names and medical record numbers from the patients' data set with AWS Glue and use AWS KMS to encrypt the data on Amazon S3.
B Replace the medical record numbers with randomly generated integers.
C Use Data Encryption Standard (DES) to hash all PHI data.
D Store the data in Aurora Medical DB.
Question # 7
A Machine Learning company intern was given a project to double the input data set used to train the model. While the previous model was performing well, with 90% accuracy, the updated model that used the expanded data set is performing much worse. What could be a possible explanation?
A Amazon has updated seq2seq algorithm.
B Expanded data set was not shuffled.
C New observations should have additional labels added.
D New observations should have been used just for validation purpose.
Question # 8
A Data Scientist is using an ML regression model to fit the data set containing thousands of features. The training times are long and the costs are escalating. What can he do to improve training time?
A Use clustering to reduce the number of features.
B Do nothing, all features might be relevant.
C Remove uncorrelated features.
D Normalize all features.
Question # 9
The optimal compromise (the most accurate in diagnosing the outcome) between sensitivity and specificity of the ROC curve is:
A The point nearest to the bottom right corner
B The intersection of the curve and specificity=1 line
C The point nearest to the top left corner (TP=1, TN=0)
D The point with sensitivity=1
Question # 10
A Machine Learning Specialist is building an ML model using the EMR cluster. He would like to test the application on a cluster processing a small, but representative subset of his data. He would also like to enable the log file writing on the master node. What he has to do?
A Set Redirect Flag=1 on S3.
B Install YARN.
C SSH to Master Node and create /mnt/var/log directory.
D Nothing, logging is enabled by default.
Question # 11
How does Leaky RELU differ from standard RELU?
A Leaky RELU has left-over digit.
B Leaky RELU has a small term with positive gradient for non-active input.
C Leaky RELU is a log of RELU
D Leaky RELU has a bias term.
Question # 12
A match-making company is developing a machine learning algorithm that will pair couples from its extensive database with more than 50k records. The dataset features include customer names, zip codes, age, height, weight, educational level, and annual income. These are 50 outliers in the income column, and 300 records are missing age info. What should a data Scientist do before training a machine learning program? (Select TWO.)
A Encode education level feature
B Convert outlier income values to log scale
C Convert zip codes to states
D Remove the age column
E Drop client first and last names
Question # 13
A Real Estate Wholesaler is seeking an ML expert who will develop ML workflow to identify potential for-sale properties. He plans to hire people to drive around the neighborhoods and stream videos of all houses in a neighborhood that could potentially be available for a quick cash sale. Which AWS services could an expert use to most easily accomplish the task?
A AWS Deep Grab->AWS Polly->AWS Notify
B Amazon Deep Lens -> Amazon Kinesis Video->AWS Sage Maker
C Amazon Comprehend- > AWQ Deep Lens -> AWS EC2
D AWS Video ->A WS Predict -> AWS Notify
Question # 14
Two variables defining ROC curve (Receiver-Operating Characteristic) are (select TWO answers):
A Recall and Precision
B F1 Score and True Negative Rate
C True Positive Rate and False Positive rate
D Sensitivity and (1-Specificity)
E Sensitivity and Specificity
Question # 15
Mark is evaluating the model performance of the binary classification problem with balanced classes. What tool would be appropriate to use?
A ROC Curve
B Mis-classification Curve
C Classification Curve
D Precision--Recall Curve
Question # 16
How to ensure Sage maker ML code containers can communicate securely?
A Turn on encryption at rest
B Run jobs in an EC2 mode
C Enable inter-container traffic encryption
D Use KMS to pass key to ML instances
Question # 17
A client is looking for experienced freelancers on an online platform. He wants to forecast the sales of his vintage clothing store that has been doing very well. His budget is limited though, and he would like to have results within a week. He has historic sales data that span the last 3 years. What approach should freelancers suggest in their proposals?
A Develop a custom ML Model using open-source Jupyter Notebook.
B Use AWS History Forward.
C Use Spark EMR cluster on historic store datasets.
D Use Amazon Forecast
Question # 18
A Visualization Specialist wants to display the results of a survey about people’s favorite kind of movie in five different categories: comedy, action, romance, drama, and SciFi. What is the best way to visualize that survey?
A Pie Chart
B Bar Histogram
C Scatter Plot
D Bubble Plot
Question # 19
A software company was contracted to develop an application that counts concert-goers at sports arena entrances and then deploy the app in real-time on Nvidia Jetson Nano devices. A developer team at the company will write a custom Amazon Sage maker model, train the model once using Amazon Neo and then run it at the edge. What are the main advantages of using Amazon Neo? (Name TWO.)
A ML model can use LSTM instances.
B Inference instances can run on multiple GPUs.
C Required framework memory is reduced 10x.
D ML models will run with up to 2x better performance.
E Algorithm can be written in Scala.
Question # 20
You are the head of the investment company’s analytics team and you are proposing to use Amazon QuickSight for visualizing your teams’ data. Which feature of Quicksight helps it to perform well under heavy load and scales to many users?
A Go Quick
B SCALE
C Heavy Duty
D SPICE
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