Trustworthy Databricks-Machine-Learning-Associate Source - Exam Dumps Databricks-Machine-Learning-Associate Demo

The last format is desktop Databricks-Machine-Learning-Associate practice test software that can be accessed easily just by installing the software on the Windows Pc or Laptop. The desktop software format can be accessed offline without any internet so the students who don't have internet won't struggle in the preparation for Databricks-Machine-Learning-Associate Exam. These three forms are specially made for the students to access them according to their comfort zone and Databricks-Machine-Learning-Associate exam prepare for the best.

On the one hand, by the free trial services you can get close contact with our products, learn about the detailed information of our Databricks-Machine-Learning-Associate study materials, and know how to choose the different versions before you buy our products. On the other hand, using free trial downloading before purchasing, I can promise that you will have a good command of the function of our Databricks-Machine-Learning-Associate Exam prepare. According to free trial downloading, you will know which version is more suitable for you in advance and have a better user experience.

>> Trustworthy Databricks-Machine-Learning-Associate Source <<

Free PDF Quiz High Hit-Rate Databricks-Machine-Learning-Associate - Trustworthy Databricks Certified Machine Learning Associate Exam Source

Perhaps the path to successful pass the Databricks-Machine-Learning-Associate is filled variables, but now there is only one possibility to successfully obtain a Databricks-Machine-Learning-Associate certification. That is to download and use our Databricks-Machine-Learning-Associate study materials. Trying to become a Databricks-Machine-Learning-Associate certified professional. Then join our preparation kit. Databricks-Machine-Learning-Associate is an excellent platform that provides an Databricks-Machine-Learning-Associate study materials that are officially equipped by an expert. Our Databricks-Machine-Learning-Associate Exam Material can be studied and passed quickly within one week of the exam. Our Databricks-Machine-Learning-Associate exam materials will give you the best knowledge of the contents of the Databricks-Machine-Learning-Associate exam certification course outline. Our Databricks-Machine-Learning-Associate materials provide you with the best learning prospects and give you more than you expect by adopting minimal effort.

Databricks Certified Machine Learning Associate Exam Sample Questions (Q60-Q65):

NEW QUESTION # 60
A data scientist is using Spark ML to engineer features for an exploratory machine learning project.
They decide they want to standardize their features using the following code block:

Upon code review, a colleague expressed concern with the features being standardized prior to splitting the data into a training set and a test set.
Which of the following changes can the data scientist make to address the concern?

A. Utilize the MinMaxScaler object to standardize the training data according to global minimum and maximum values
B. Utilize the MinMaxScaler object to standardize the test data according to global minimum and maximum values
C. Utilize the Pipeline API to standardize the test data according to the training data's summary statistics
D. Utilize a cross-validation process rather than a train-test split process to remove the need for standardizing data
E. Utilize the Pipeline API to standardize the training data according to the test data's summary statistics

Answer: C

Explanation:
To address the concern about standardizing features prior to splitting the data, the correct approach is to use the Pipeline API to ensure that only the training data's summary statistics are used to standardize the test data. This is achieved by fitting the StandardScaler (or any scaler) on the training data and then transforming both the training and test data using the fitted scaler. This approach prevents information leakage from the test data into the model training process and ensures that the model is evaluated fairly.
Reference:
Best Practices in Preprocessing in Spark ML (Handling Data Splits and Feature Standardization).

NEW QUESTION # 61
A data scientist has created a linear regression model that uses log(price) as a label variable. Using this model, they have performed inference and the predictions and actual label values are in Spark DataFrame preds_df.
They are using the following code block to evaluate the model:
regression_evaluator.setMetricName("rmse").evaluate(preds_df)
Which of the following changes should the data scientist make to evaluate the RMSE in a way that is comparable with price?

A. They should exponentiate the computed RMSE value
B. They should exponentiate the predictions before computing the RMSE
C. They should take the log of the predictions before computing the RMSE
D. They should evaluate the MSE of the log predictions to compute the RMSE

Answer: B

Explanation:
When evaluating the RMSE for a model that predicts log-transformed prices, the predictions need to be transformed back to the original scale to obtain an RMSE that is comparable with the actual price values. This is done by exponentiating the predictions before computing the RMSE. The RMSE should be computed on the same scale as the original data to provide a meaningful measure of error.
Reference:
Databricks documentation on regression evaluation: Regression Evaluation

NEW QUESTION # 62
A data scientist has developed a linear regression model using Spark ML and computed the predictions in a Spark DataFrame preds_df with the following schema:
prediction DOUBLE
actual DOUBLE
Which of the following code blocks can be used to compute the root mean-squared-error of the model according to the data in preds_df and assign it to the rmse variable?

Answer: B

Explanation:
To compute the root mean-squared-error (RMSE) of a linear regression model using Spark ML, the RegressionEvaluator class is used. The RegressionEvaluator is specifically designed for regression tasks and can calculate various metrics, including RMSE, based on the columns containing predictions and actual values.
The correct code block to compute RMSE from the preds_df DataFrame is:
regression_evaluator = RegressionEvaluator( predictionCol="prediction", labelCol="actual", metricName="rmse" ) rmse = regression_evaluator.evaluate(preds_df) This code creates an instance of RegressionEvaluator, specifying the prediction and label columns, as well as the metric to be computed ("rmse"). It then evaluates the predictions in preds_df and assigns the resulting RMSE value to the rmse variable.
Options A and B incorrectly use BinaryClassificationEvaluator, which is not suitable for regression tasks. Option D also incorrectly uses BinaryClassificationEvaluator.
Reference:
PySpark ML Documentation

NEW QUESTION # 63
Which of the Spark operations can be used to randomly split a Spark DataFrame into a training DataFrame and a test DataFrame for downstream use?

A. TrainValidationSplit
B. CrossValidator
C. DataFrame.where
D. TrainValidationSplitModel
E. DataFrame.randomSplit

Answer: E

Explanation:
The correct method to randomly split a Spark DataFrame into training and test sets is by using the randomSplit method. This method allows you to specify the proportions for the split as a list of weights and returns multiple DataFrames according to those weights. This is directly intended for splitting DataFrames randomly and is the appropriate choice for preparing data for training and testing in machine learning workflows.
Reference:
Apache Spark DataFrame API documentation (DataFrame Operations: randomSplit).

NEW QUESTION # 64
Which of the following tools can be used to distribute large-scale feature engineering without the use of a UDF or pandas Function API for machine learning pipelines?

A. PvTorch
B. pandas
C. Scikit-learn
D. Keras
E. Spark ML

Answer: E

Explanation:
Spark ML (Machine Learning Library) is designed specifically for handling large-scale data processing and machine learning tasks directly within Apache Spark. It provides tools and APIs for large-scale feature engineering without the need to rely on user-defined functions (UDFs) or pandas Function API, allowing for more scalable and efficient data transformations directly distributed across a Spark cluster. Unlike Keras, pandas, PyTorch, and scikit-learn, Spark ML operates natively in a distributed environment suitable for big data scenarios.
Reference:
Spark MLlib documentation (Feature Engineering with Spark ML).

NEW QUESTION # 65
......

Like other Databricks examinations, the Databricks-Machine-Learning-Associate exam preparation calls for a strong preparation and precise Databricks-Machine-Learning-Associate practice material. Finding original and latest 121 exam questions however, is a difficult process. Candidates require assistance finding the Databricks-Machine-Learning-Associate updated questions. It will be hard for applicants to pass the Databricks Databricks-Machine-Learning-Associate exam on their first try if Databricks Certified Machine Learning Associate Exam questions they have are not real and updated.

Exam Dumps Databricks-Machine-Learning-Associate Demo: https://www.vcetorrent.com/Databricks-Machine-Learning-Associate-valid-vce-torrent.html

Databricks Trustworthy Databricks-Machine-Learning-Associate Source The purchase procedures are safe and we protect our client’s privacy, Databricks Trustworthy Databricks-Machine-Learning-Associate Source How do I pay for my order, Databricks Trustworthy Databricks-Machine-Learning-Associate Source If you buy our test dumps insides, you can not only pass exams but also enjoy a year of free update service, Before you decide to buy the materials, you can download some of the Databricks-Machine-Learning-Associate questions and answers.

Cells going left to right horizontally) in Databricks-Machine-Learning-Associate a row have an X coordinate, Its extrinsic or instrumental function is to encourage and facilitate the development of students Latest Databricks-Machine-Learning-Associate Test Blueprint and help make them helpful to others and self-supporting members of society.

Databricks Databricks-Machine-Learning-Associate Exam Practice Questions are Real and Verified By Experts

The purchase procedures are safe and we protect our client’s privacy, Databricks-Machine-Learning-Associate Test Dump How do I pay for my order, If you buy our test dumps insides, you can not only pass exams but also enjoy a year of free update service.

Before you decide to buy the materials, you can download some of the Databricks-Machine-Learning-Associate Questions and answers, At last, in order to save time and adapt the actual test in advance, most people prefer to choose the Databricks-Machine-Learning-Associate online test engine for their test preparation.

Will Cook Will Cook

Biography

Trustworthy Databricks-Machine-Learning-Associate Source - Exam Dumps Databricks-Machine-Learning-Associate Demo

Free PDF Quiz High Hit-Rate Databricks-Machine-Learning-Associate - Trustworthy Databricks Certified Machine Learning Associate Exam Source

Databricks Certified Machine Learning Associate Exam Sample Questions (Q60-Q65):

Databricks Databricks-Machine-Learning-Associate Exam Practice Questions are Real and Verified By Experts

Company

Quick Links

Work with us

For Businesses

© 2017 - 2021 Fresher2Expert. All rights reserved

Admissions Enquiry: 9903535635