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Put your Scala knowledge to good use by tackling Big Data analytics problems. Learn to leverage the integration of Apache Spark™ and Scala. Learn how use Spark’s machine learning pipelines to fit models and search for optimal hyperparameters using Scala in a Spark cluster.
Module 1: Basic Statistics and Data Types
Question: You import MLlib’s vectors from ?
Question: Select the types of distributed Matrices :
Question: How would you caculate the mean of the following ?
val observations: RDD[Vector] = sc.parallelize(Array(
Vectors.dense(1.0, 2.0),
Vectors.dense(4.0, 5.0),
Vectors.dense(7.0, 8.0)))
val summary: MultivariateStatisticalSummary = Statistics.colStats(observations)
Question: what task does the following lines of code?
import org.apache.spark.mllib.random.RandomRDDs._
val million = poissonRDD(sc, mean=1.0, size=1000000L, numPartitions=10)
Question: MLlib uses the compressed sparse column format for sparse matrices, as Such it only keeps the non-zero entrees?
Module 2: Preparing Data
Question: WFor a dataframe object the method describe calculates the ?
Question: What line of code drops the rows that contain null values, select the best answer ?
Question: What task does the following lines of code perform ?
val lr = new LogisticRegression()
lr.setMaxIter(10).setRegParam(0.01)
val model1 = lr.fit(training)
Question: The StandardScaleModel transforms the data such that ?
Module 3: Feature Engineering
Question: Spark ML works with?
Question: the function IndexToString()
performs One hot encoding?
Question: Principal Component Analysis is Primarily used for ?
Question: one import set prior to using PCA is ?
Module 4: Fitting a Model
Question: You can use decision trees for ?
Question: the following lines of code: val Array(trainingData, testData) = data.randomSplit(Array(0.7, 0.3))
Question: in the Random Forest Classifier constructor .setNumTrees() ?
Question: Elastic net regularization uses ?
Module 5: Pipeline and Grid Search
Question: what task does the following code perform: withColumn("paperscore", data("A2") * 4 + data("A") * 3)
?
Question: In an estimator ?
Question: Which is not a valid type of Evaluator in MLlib?
Question: In the following lines of code, the last transform in the pipeline is a:
val rf = new RandomForestClassifier().setFeaturesCol(“assembled”).setLabelCol(“status”).setSeed(42)
import org.apache.spark.ml.Pipeline
val pipeline = new Pipeline().setStages(Array(value_band_indexer,category_indexer,label_indexer,assembler,rf))
Final Exam
Question: What is not true about labeled points?
Question: Which is true about column pointers in sparse matrices?
Question: What is the name of the most basic type of distributed matrix?
Question: A perfect correlation is represented by what value?
Question: A MinMaxScaler is a transformer which:
Question: Which is not a supported Random Data Generation distribution?
Question: Sampling without replacement means:
Question: What are the supported types of hypothesis testing?
Question: For Kernel Density Estimation, which kernel is supported by Spark?
Question: Which DataFrames statistics method computes the pairwise frequency table of the given columns?
Question: Which is not true about the fill method for DataFrame NA functions?
Question: Which transformer listed below is used for Natural Language processing?
Question: Which is true about the Mahalanobis Distance?
Question: Which is true about OneHotEncoder?
Question: Principle Component Analysis is:
Question: MLlib’s implementation of decision trees:
Question: Which is not a tunable of SparkML decision trees?
Question: Which is true about Random Forests?
Question: When comparing Random Forest versus Gradient-Based Trees, what must you consider?
Question: Which is not a valid type of Evaluator in MLlib?
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