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Apache SystemML is a declarative style language designed for large-scale machine learning. It automatically generates optimized runtime plans, from single-node to in-memory, to distributed computations on Apache Hadoop and Apache Spark. SystemML algorithms are expressed in R-like or Python-like syntax, including linear algebra primitives, statistical functions, and ML-specific constructs. Any changes you want!

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Cognitive Class: Machine learning with Apache SystemML Exam Answers

Module 1 – What is SystemML? Answers

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

  1. True
  2. False

2. Which of the following are types of alternatives to SystemML?

  1. R
  2. MLlib
  3. Spark R
  4. Mahout
  5. All of the above

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

  1. True
  2. False

Module 2 – SystemML and the Spark MLContext Answers

1. What the ways you can use SystemML’s Spark MLContext?

  1. spark-shell
  2. Through an application using the API
  3. Through the SystemML console
  4. A notebook interface
  5. None of the above

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

  1. True
  2. False

3. Why would you use the Spark MLContext?

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

Module 3 – SystemML algorithms Answers

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

  1. True
  2. False

2. 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.

  1. True
  2. False

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

  1. True
  2. False

Module 4 – Declarative Machine Learning (DML) Answers

1. What does DML stand for?

  1. Data manipulation language
  2. Data machine language
  3. Declarative machine learning
  4. Declarative machine language

2. To run a DML script, which of the following jar file is required at runtime?

  1. MLContext.jar
  2. DML.jar
  3. SystemML.jar
  4. spark-context.jar

3. Which of the following way to pass command-line arguments is recommended?

  1. positional arguments
  2. named arguments
  3. a comma separated list
  4. a file

Module 5 – SystemML architecture and optimization Answers

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

  1. Large
  2. Medium
  3. Small
  4. None

2. Which of the following does NOT belong to the SystemML Optimizer stack?

  1. Create the RDDs for the high level algorithm
  2. Compute memory estimates
  3. Generate runtime program
  4. Live variable analysis

3. How does SystemML know it is better to run the code on one machine?

  1. Advanced Rewrites
  2. Propagation of statistics
  3. Live variable analysis
  4. Efficient runtime
  5. The developer tells it to

Machine learning with Apache SystemML Final Exam Answers

1. What is machine learning?

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

2. What is the purpose of SystemML?

  1. Programming language for big data
  2. In-memory analytics engine
  3. Machine learning for spark
  4. Machine learning on hadoop
  5. All of the above

3. What are the challenges of machine learning on big data using R?

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

4. What is the vision of SystemML?

  1. Run the same algorithm developed for small data on big data
  2. Provide flexible algorithm of ML algorithms
  3. Automatic generation of hybrid runtime plans
  4. All of the above

5. Which of the following languages is SystemML most similar?

  1. R
  2. Python
  3. Java
  4. Scala
  5. Perl
  6. R and Python
  7. Java and Scala

6. Which of the following line of code will launch the Spark shell with SystemML?

  1. ./bin/spark-shell –jars SystemML.jar
  2. ./bin/spark-shell –executor-memory 4G –jars SystemML.jar
  3. ./bin/spark-shell –driver-memory 4G –jars SystemML.jar
  4. ./bin/spark-shell –executor-memory 4G –driver-memory 4G –jars SystemML.jar
  5. All of the above

7. Why would you convert a DataFrame to a binary-block matrix?

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

8. Which of the following is TRUE with regards to helper methods in SystemML?

  1. SystemML’s output is encapsulated in the MLContext object
  2. SystemML’s output is encapsulated in the MLOutput object
  3. Helper methods retrieves the values from the MLOutput object
  4. Helper methods retrieves the values from the MLContext object
  5. A and D only
  6. B and C only

9. Which is NOT a benefit of using SystemML algorithms?

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

10. Which of the following classes of algorithms provide a recommendation?

  1. Regression
  2. Classification
  3. Matrix Factorization
  4. Descriptive statistics

11. Which of the following algorithm can group a set of data into known categories?

  1. Regression
  2. Clustering
  3. Survival Analysis
  4. Classification

12. Which of the following algorithm can be used for prediction, forecasting, or error reduction?

  1. Clustering
  2. Regression
  3. Survival Analysis
  4. Descriptive statistics

13. Which of the following value typesis NOT supported in the DML language?

  1. String
  2. Double
  3. Varchar
  4. Boolean

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

  1. True
  2. False

15. Global variables cannot be access within a function. True or false?

  1. True
  2. False

16. Which of the following are NOT types of categories of built-in functions in DML?

  1. Derivative built-in functions
  2. Matrix built-in functions
  3. Statistical built-in functions
  4. Casting built-in functions

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

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

18. What is the benefit of doing the matrix rewrite?

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

19. Which is NOT part of the SystemML runtime for Spark?

  1. Automates critical performance decisions
  2. Distributed vs. local runtime
  3. Efficient linear algebra optimizations
  4. Automated RDD caching
  5. None of the above

20. SystemML is an Apache open source project. True or false

  1. True
  2. False

Wrap Up

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