A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users' behavior and product preferences to predict which products users would like based on the users' similarity to other users.
What should the Specialist do to meet this objective?

• A.Build a content-based filtering recommendation engine with Apache Spark ML on Amazon EMR
• B.Build a collaborative filtering recommendation engine with Apache Spark ML on Amazon EMR.
• C.Build a model-based filtering recommendation engine with Apache Spark ML on Amazon EMR
• D.Build a combinative filtering recommendation engine with Apache Spark ML on Amazon EMR

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A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs What does the Specialist need to do1?

• A.Organize the Docker container's file structure to execute on GPU instances.
• B.Bundle the NVIDIA drivers with the Docker image
• C.Set the GPU flag in the Amazon SageMaker Create TrainingJob request body
• D.Build the Docker container to be NVIDIA-Docker compatible

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A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of test results. The Data Scientist has data on 400 patients randomly selected from the population. The disease is seen in 3% of the population.
Which cross-validation strategy should the Data Scientist adopt?

• A.A k-fold cross-validation strategy with k=5
• B.A stratified k-fold cross-validation strategy with k=5
• C.A k-fold cross-validation strategy with k=5 and 3 repeats
• D.An 80/20 stratified split between training and validation

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An agency collects census information within a country to determine healthcare and social program needs by province and city. The census form collects responses for approximately 500 questions from each citizen Which combination of algorithms would provide the appropriate insights? (Select TWO )

• A.The factorization machines (FM) algorithm
• B.The Latent Dirichlet Allocation (LDA) algorithm
• C.The principal component analysis (PCA) algorithm
• D.The k-means algorithm
• E.The Random Cut Forest (RCF) algorithm

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This graph shows the training and validation loss against the epochs for a neural network The network being trained is as follows
* Two dense layers one output neuron
* 100 neurons in each layer
* 100 epochs
* Random initialization of weights

Which technique can be used to improve model performance in terms of accuracy in the validation set?

• A.Adding another layer with the 100 neurons
• B.Early stopping
• C.Random initialization of weights with appropriate seed
• D.Increasing the number of epochs

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