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These are the answers to Machine learning with Apache System ML Cognitive Class Course Quiz Answers certification course. These answers have been updated recently and are 100% correct. The final exam is on Monday, April. All answers are 100%.

Module 1 – What is SystemML?

Question1: Which of the following are types of alternatives to SystemML?

• R
• MLlib
• Spark R
• Mahout
• All of the above

Question2: In machine learning, as analytical models are exposed to new data, they are able to independently adapt. True or false?

• True
• False

Question3: The R language was designed for machine learning and works great for big data. True or false?

• True
• False

Module 2 – SystemML and the Spark MLContex

Question 1: Why would you use the Spark MLContext?

• Programmatic interface into SystemML’s libraries
• To benefit from the optimizations that come with SystemML
• When you need to convert the data to a binary block matrix
• A and B only
• None of the above

Question 2: What the ways you can use SystemML’s Spark MLContext?

• spark-shell
• Through an application using the API
• Through the SystemML console
• A notebook interface
• None of the above

Question 3: You must pass in the reference of the SparkContext to the MLContext constructor. True or false?

• True
• False

Module 3 – SystemML algorithms

Question1: The Classification algorithm of ensemble learning method that creates a model composed of a set of tree models for classification. True or false?

• True
• False

Question2: The Kaplan-Meier algorithm predicts how likely it is someone will purchase a product of similar category. True or false?

• True
• False

Question3: K-means is an unsupervised learning algorithm used to assign a category label to each record so that each similar record tend to get the same label. True or false.

• True
• False

Module 4 – Declarative Machine Learning (DML)

Question 1: To run a DML script, which of the following jar file is required at runtime?

• MLContext.jar
• DML.jar
• SystemML.jar
• spark-context.jar

Question 2:Which of the following way to pass command-line arguments is recommended?

• positional arguments
• named arguments
• a comma separated list
• a file

Question 3: What does DML stand for?

• Data manipulation language
• Data machine language
• Declarative machine learning
• Declarative machine language

Module 5 – SystemML architecture and optimization

Question 1 : In the ALS performance comparison, at which dataset does the MLlib code run out of memory??

• Large
• Medium
• Small
• None

Question 2 : How does SystemML know it is better to run the code on one machine?

• Advanced Rewrites
• Propagation of statistics
• Live variable analysis
• Efficient runtime
• The developer tells it to

Question 3 : Which of the following does NOT belong to the SystemML Optimizer stack?

• Create the RDDs for the high level algorithm
• Compute memory estimates
• Generate runtime program
• Live variable analysis

Final Exam :

Question 1 : What is machine learning?

• Artificial intelligence for machines to make decisions
• Same as data science to gather insight using machines
• Enable computers to learn without being explicitly programmed
• Learning about how machines operate

Question 2 : Which is NOT part of the SystemML runtime for Spark?

• Automates critical performance decisions
• Distributed vs. local runtime
• Efficient linear algebra optimizations
• Automated RDD caching
• None of the above

Question 3 : Which of the following is TRUE with regards to helper methods in SystemML?

• SystemML’s output is encapsulated in the MLContext object
• SystemML’s output is encapsulated in the MLOutput object
• Helper methods retrieves the values from the MLOutput object
• Helper methods retrieves the values from the MLContext object
• A and D only
• B and C only

Question 4 : What is the purpose of SystemML?

• Programming language for big data
• In-memory analytics engine
• Machine learning for spark
• Machine learning on hadoop
• All of the above

Question 5 : Which of the following classes of algorithms provide a recommendation?

• Regression
• Classification
• Matrix Factorization
• Descriptive statistics

Question 6 : SystemML is an Apache open source project. True or false

• True
• False

Question 7 : Global variables cannot be access within a function. True or false?

• True
• False

Question 8 : Why would you convert a DataFrame to a binary-block matrix?

• To enable parallelization within the Spark engine
• To use the rich set of APIs provided by the binary-block matrix
• Allows algorithm performance to be measured separately from data conversion time
• Allows a more efficient runtime processing of the data

Question 9 : Matrix-vector operations avoids the need for creating replicated matrix for a certain subset of operations. True or false?

• True
• False

Question 10 : What is the benefit of doing the matrix rewrite?

• Reduce the line of code needed to represent the matrix
• To determine the confidence level of the computed results
• Clean up and unused memory from the matrix
• To enable parallelization of the given matrixithin a given period of time
• Represent the final matrix without computing the intermediate matrices

Question 11 : What are the challenges of machine learning on big data using R?

• Programmers are needed to convert the high level code to low level code for parallel computing
• Each iteration of the code takes time to be rewritten and recompile
• Chances for errors are higher during the translation of the algorithms
• All of the above

Question 12 : What is the vision of SystemML?

• Run the same algorithm developed for small data on big data
• Provide flexible algorithm of ML algorithms
• Automatic generation of hybrid runtime plans
• All of the above

Question 13 : Which of the following are NOT types of categories of built-in functions in DML?

• Derivative built-in functions
• Matrix built-in functions
• Statistical built-in functions
• Casting built-in functions

Question 14 : Which is NOT a benefit of using SystemML algorithms?

• Run in parallel
• It is faster than all other algorithms
• No need for translation into a lower level language
• Algorithms are optimized based on data and cluster characteristics

Question 15 : Which of the following algorithm can group a set of data into known categories?

• Regression
• Clustering
• Survival Analysis
• Classification

Question 16 : Which of the following languages is SystemML most similar?

• R
• Python
• Java
• Scala
• Perl
• R and Python
• Java and Scala

Question 17 : In the statistics propagation phase of the SystemML optimizer, what exactly is happening?

• To determine the confidence level of the computed results
• All the statistics is propagated to the top node to determine the most efficient runtime for query execution
• To determine of probability of the operation succeeding within a given period of time
• Find the widest matrix required and determine if it all fits into the heap.

Question 18 : Which of the following algorithm can be used for prediction, forecasting, or error reduction?

• Clustering
• Regression
• Survival Analysis
• Descriptive statistics

Question 19: Which of the following line of code will launch the Spark shell with SystemML?

• ./bin/spark-shell –jars SystemML.jar
• ./bin/spark-shell –executor-memory 4G –jars SystemML.jar
• ./bin/spark-shell –driver-memory 4G –jars SystemML.jar
• ./bin/spark-shell –executor-memory 4G –driver-memory 4G –jars SystemML.jar
• All of the above

Question 20 : Which of the following value typesis NOT supported in the DML language?

• String
• Double
• Varchar
• Boolean

Conclusion

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