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你也會很快很順利的通過Amazon MLS-C01考試證照綜述的認證考試。
我們Goldmile-Infobiz是一家專業的IT認證網站,它的認證成功率達到100%,許多考生實踐證明了的,因為我們Goldmile-Infobiz擁有一支強大的IT專家隊伍,他們致力於廣大考生的考試題及答案,為廣大考生的切身利益而服務,用自己專業的頭腦和豐富的經驗來滿足考生們的需求,根據考生的需求從各個角度出發,針對性的設計適用性強的考試培訓資料,也就是 Amazon的MLS-C01 - AWS Certified Machine Learning - Specialty考試證照綜述考試培訓資料,包括試題及答案。 Goldmile-Infobiz是一個對Amazon 最新 MLS-C01 考題 認證考試提供針對性培訓的網站。Goldmile-Infobiz也是一個不僅能使你的專業知識得到提升,而且能使你一次性通過Amazon 最新 MLS-C01 考題 認證考試的網站。
上帝讓我成為一個有實力的人,而不是一個好看的布娃娃。當我選擇了IT行業的時候就已經慢慢向上帝證明了我的實力,可是上帝是個無法滿足的人,逼著我一直向上。這次通過 Amazon的MLS-C01考試證照綜述考試認證是我人生中的一大挑戰,所以我拼命的努力學習,不過不要緊,我購買了Goldmile-Infobiz Amazon的MLS-C01考試證照綜述考試認證培訓資料,有了它,我就有了實力通過 Amazon的MLS-C01考試證照綜述考試認證,選擇Goldmile-Infobiz培訓網站只說明,路在我們腳下,沒有人決定它的方向,擁有了Goldmile-Infobiz Amazon的MLS-C01考試證照綜述考試培訓資料,就等於擁有了一個美好的未來。
Amazon MLS-C01考試證照綜述 - 你绝对会相信我的话的。
很多IT人士都想通過Amazon MLS-C01考試證照綜述 認證考試,從而在IT行業中獲取更好的提升機會,使他們的工資生活水準都有所提升。但是好多人為了通過Amazon MLS-C01考試證照綜述 認證考試花了大量時間和精力來鞏固相關知識卻沒有通過考試。這樣是很不划算。如果你選擇Goldmile-Infobiz的產品,你可以為你節約很多時間和精力來鞏固知識,但是卻可以通過Amazon MLS-C01考試證照綜述 認證考試。因為Goldmile-Infobiz的關於Amazon MLS-C01考試證照綜述 認證考試的針對性的資料可以幫助你100%通過考試。如果你考試失敗,Goldmile-Infobiz會全額退款給你。
只要你選對了工具,成功簡直就是一件輕而易舉的事情。你想知道什麼工具最好嗎?現在告訴你。
MLS-C01 PDF DEMO:
QUESTION NO: 1
A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.
What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?
A. Receiver operating characteristic (ROC) curve
B. Misclassification rate
C. Root Mean Square Error (RM&)
D. L1 norm
Answer: A
QUESTION NO: 2
A Machine Learning Specialist built an image classification deep learning model. However the
Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and
75%r respectively.
How should the Specialist address this issue and what is the reason behind it?
A. The learning rate should be increased because the optimization process was trapped at a local minimum.
B. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
C. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.
D. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
Answer: C
QUESTION NO: 3
A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers Currently, the company has the following data in
Amazon Aurora
* Profiles for all past and existing customers
* Profiles for all past and existing insured pets
* Policy-level information
* Premiums received
* Claims paid
What steps should be taken to implement a machine learning model to identify potential new customers on social media?
A. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
B. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
C. Use regression on customer profile data to understand key characteristics of consumer segments
Find similar profiles on social media.
D. Use clustering on customer profile data to understand key characteristics of consumer segments
Find similar profiles on social media.
Answer: B
QUESTION NO: 4
A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.
The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:
* Real-time analytics
* Interactive analytics of historical data
* Clickstream analytics
* Product recommendations
Which services should the Specialist use?
A. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations
B. AWS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
C. AWS Glue as the data dialog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
D. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS
Glue to generate personalized product recommendations
Answer: C
QUESTION NO: 5
A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.
Which of the following methods should the Specialist consider using to correct this? (Select THREE.)
A. Decrease dropout.
B. Increase regularization.
C. Increase feature combinations.
D. Decrease feature combinations.
E. Decrease regularization.
F. Increase dropout.
Answer: A,B,C
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Updated: May 28, 2022