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AWS Certified Specialty MLS-C01 何の問題があったらお気軽に聞いてください。
調査、研究を経って、IT職員の月給の増加とジョブのプロモーションはAmazon MLS-C01 - AWS Certified Machine Learning - Specialty資格取得講座資格認定と密接な関係があります。 それに、あなたに極大な便利と快適をもたらせます。実践の検査に何度も合格したこのサイトは試験問題と解答を提供しています。
この目標の達成はあなたがIT技術領域へ行く更なる発展の一歩ですけど、我々社Goldmile-Infobiz存在するこそすべての意義です。だから、我々社は力の限りで弊社のAmazon MLS-C01資格取得講座試験資料を改善し、改革の変更に応じて更新します。あなたはいつまでも最新版の問題集を使用できるために、ご購入の一年間で無料の更新を提供します。
Amazon MLS-C01資格取得講座 - 君の夢は1歩更に近くなります。
MLS-C01資格取得講座認定試験はたいへん難しい試験ですね。しかし、難しい試験といっても、試験を申し込んで受験する人が多くいます。なぜかと言うと、もちろんMLS-C01資格取得講座認定試験がとても大切な試験ですから。IT職員の皆さんにとって、この試験のMLS-C01資格取得講座認証資格を持っていないならちょっと大変ですね。この認証資格はあなたの仕事にたくさんのメリットを与えられ、あなたの昇進にも助けになることができます。とにかく、これは皆さんのキャリアに大きな影響をもたらせる試験です。こんなに重要な試験ですから、あなたも受験したいでしょう。
Goldmile-Infobizの助けのもとで君は大量のお金と時間を费やさなくても復楽にAmazonのMLS-C01資格取得講座認定試験に合格のは大丈夫でしょう。ソフトの問題集はGoldmile-Infobizが実際問題によって、テストの問題と解答を分析して出来上がりました。
MLS-C01 PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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
QUESTION NO: 4
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: 5
A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s) Which visualization will accomplish this?
A. A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor
Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
B. A scatter plot showing (he performance of the objective metric over each training iteration
C. A histogram showing whether the most important input feature is Gaussian.
D. A scatter plot showing the correlation between maximum tree depth and the objective metric.
Answer: A
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Updated: May 28, 2022