Are you looking for Machine learning with Apache SystemML Exam Answers by Cognitive Class? If yes, this article will help you find all the questions and answers in the Cognitive Class Machine Learning with Apache SystemML Quiz. I have followed this article for all the questions in this exam.
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!
|Min % To Pass||70%|
|Final exam % To Pass||50%|
|Review questions % To Pass||50%|
|Max Attempt For Each Question||1/2|
|Machine learning with Apache SystemML||Click Here|
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?
2. Which of the following are types of alternatives to SystemML?
3. The R language was designed for machine learning and works great for big data. True or false?
Module 2 – SystemML and the Spark MLContext Answers
1. What the ways you can use SystemML’s Spark MLContext?
2. You must pass in the reference of the SparkContext to the MLContext constructor. True or false?
3. Why would you use the Spark MLContext?
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?
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.
3. The Kaplan-Meier algorithm predicts how likely it is someone will purchase a product of similar category. True or false?
Module 4 – Declarative Machine Learning (DML) Answers
1. What does DML stand for?
2. To run a DML script, which of the following jar file is required at runtime?
3. Which of the following way to pass command-line arguments is recommended?
Module 5 – SystemML architecture and optimization Answers
1. In the ALS performance comparison, at which dataset does the MLlib code run out of memory??
2. Which of the following does NOT belong to the SystemML Optimizer stack?
3. How does SystemML know it is better to run the code on one machine?
Machine learning with Apache SystemML Final Exam Answers
1. What is machine learning?
2. What is the purpose of SystemML?
3. What are the challenges of machine learning on big data using R?
4. What is the vision of SystemML?
5. Which of the following languages is SystemML most similar?
6. Which of the following line of code will launch the Spark shell with SystemML?
7. Why would you convert a DataFrame to a binary-block matrix?
8. Which of the following is TRUE with regards to helper methods in SystemML?
9. Which is NOT a benefit of using SystemML algorithms?
10. Which of the following classes of algorithms provide a recommendation?
11. Which of the following algorithm can group a set of data into known categories?
12. Which of the following algorithm can be used for prediction, forecasting, or error reduction?
13. Which of the following value typesis NOT supported in the DML language?
14. Matrix-vector operations avoids the need for creating replicated matrix for a certain subset of operations. True or false?
15. Global variables cannot be access within a function. True or false?
16. Which of the following are NOT types of categories of built-in functions in DML?
17. In the statistics propagation phase of the SystemML optimizer, what exactly is happening?
18. What is the benefit of doing the matrix rewrite?
19. Which is NOT part of the SystemML runtime for Spark?
20. SystemML is an Apache open source project. True or false
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