Google Cloud Certification Learning
Path- Professional Machine Learning
Engineer Exam Rated A+ Verified 2024
0.0 and 1.0 - ANSWER-The learning rate is a configurable hyperparameter used in the
training of neural networks that has a small positive value, often in the range between
_______
1. Entity extraction
2. text classification
3. sentiment analysis - ANSWER-What are the NLP tasks solved by AutoML?
1. Ingest streaming results,
2. Process data
3. Visualize results - ANSWER-Streaming data workflow steps
5% - ANSWER-What percent of system code does the ML model account for?
80-10-10 - ANSWER-Default setting in AutoML for the data split in model evaluation
A data source constructs a Dataset from data stored in memory or in one or more files
and a data transformation constructs a dataset from one or more tf.data.Dataset
objects. - ANSWER-Distinct way to create a dataset
A Google Cloud Storage bucket that acts as an input for both AutoML and custom
training jobs - ANSWER-Vertex AI has a unified data reparation tool that supports
image, tabular, text and video content. Where are uploaded datasets stored in Vertex
AI?
A large learning rate value may result in the model learning a sub-optimal set of weights
too fast or an unstable training process - ANSWER-The learning rate is a
hyperparameter that controls how much to change the model in response to the
estimated error each time the model weights are updated. Choosing the learning rate is
challenging. What can happen if the value is too large?
A large number of parameters comes from the dense layers at the end, and the
convolutional layers contain far fewer parameters - ANSWER-What is the proportion of
the number of parameters in the entire network while computing
A standard LSTM cell includes three gates: the forget gate to forget irrelevant
information, the input gate to remember relevant information, and the update gate to
,update new information. - ANSWER-What are the major gates in a standard LSTM
(long short-term memory) cell?
A task to be performed and a docker container to be executed - ANSWER-Kubeflow
tasks are organized into a dependency graph where each node represents
Ability to scale to a large dataset, find good features, it should be able to preprocess
with vertex AI - ANSWER-Which of the following are the requirements to build an
effective machine learning model?
Accounting and summarizing, anomaly detection, statistical analysis and clustering -
ANSWER-Components of EDA
Adding dropout layers to NN - ANSWER-How does regularization help build
generalizable models
adds the sum of the squared parameter weights term to the loss function - ANSWER-
The L2 regularization provides:
after turning your raw data into a useful feature vector - ANSWER-In what form can raw
data b used inside ML models?
An RNN uses a mechanism called hidden state to carry the previous information to the
next learning iteration. - ANSWER-What is the key feature to enable a "memory" of an
RNN (recurrent neural network)?
Analytics Hub - ANSWER-_________- efficiently and securely exchanges data analytics
assets across organizations to address challenges of data reliability and cost. You can
create and access a curated library of internal and external assets, including unique
datasets like Google Trends, backed by the power of BigQuery. There are three roles in
_____________ - A Data Publisher, Exchange Administrator, and a Data Subscriber.
Apache and TF - ANSWER-What is TensorFlow Transform a hybrid of?
Archive storage - ANSWER-Which data storage class is best for storing data that needs
to be accessed less than once a year, such as online backups and disaster recovery?
Ask the user for some basic preferences. Rely on content-based method instead for
new users - ANSWER-What are some ways you can address the cold-start problem
that can occur for new users of a collaborative filter recommendation system? There
could be more than one answer.
AutoML - ANSWER-What method do you use to create and train a model with minimal
technical effort to quickly prototype models and explore new datasets before investing in
development?
, AutoML - ANSWER-Your company has a lot of data, and you want to train your own
machine model to see what insights ML can provide. Due to resource constraints, you
require a codeless solution. Which option is best?
AutoML, which is a no-code solution, and custom training, which is a code-based
solution - ANSWER-Vertex AI provides two solutions to build an NLP project. Which of
the following is correct about these two solutions?
Avoid training server skew, avoid target leakage, provide a time signal - ANSWER-What
are the best practices for data prep?
Avoids overfitting - ANSWER-Why is regularization important in logistic regression?
Batch Load - ANSWER-Which pattern describes source data that is moved into BQ
table in a single operation?
Batch Normalization - ANSWER-_______________ applies a transformation that
maintains the mean output close to 0 and the output standard deviation close to 1
Batch serving and online serving - ANSWER-What are the two methods feature store
offers for serving features?
Big Query ML - ANSWER-For a user who can use SQL, has little Machine Learning
experience and wants a 'Low-Code' solution, which Machine Learning framework
should they use?
Both Labeled and Unlabeled data - ANSWER-Refers to the type of data used in ML
models
Both updating network weights iteratively based on training data by diagonal rescaling
of the gradients - ANSWER-how does Adam help in compiling the Keras model
BQ manages the underlying structure - ANSWER-BQ is a fully managed data
warehouse, what does fully managed refer to?
BQ ML - ANSWER-You work for a global hotel chain that has recently loaded some
guest data into BigQuery. You have experience writing SQL and want to leverage
machine learning to help predict guest trends for the next few months. Which option is
best?
By using the outputs of a component as an input of another component - ANSWER-
How can you define the pipelines workflow as a graph?
Categorical features preprocessing - ANSWER-tf.keras.layers.CategoryEncoding,
tf.keras.layers.Hashing, tf.keras.layers.IntegerLookup
Path- Professional Machine Learning
Engineer Exam Rated A+ Verified 2024
0.0 and 1.0 - ANSWER-The learning rate is a configurable hyperparameter used in the
training of neural networks that has a small positive value, often in the range between
_______
1. Entity extraction
2. text classification
3. sentiment analysis - ANSWER-What are the NLP tasks solved by AutoML?
1. Ingest streaming results,
2. Process data
3. Visualize results - ANSWER-Streaming data workflow steps
5% - ANSWER-What percent of system code does the ML model account for?
80-10-10 - ANSWER-Default setting in AutoML for the data split in model evaluation
A data source constructs a Dataset from data stored in memory or in one or more files
and a data transformation constructs a dataset from one or more tf.data.Dataset
objects. - ANSWER-Distinct way to create a dataset
A Google Cloud Storage bucket that acts as an input for both AutoML and custom
training jobs - ANSWER-Vertex AI has a unified data reparation tool that supports
image, tabular, text and video content. Where are uploaded datasets stored in Vertex
AI?
A large learning rate value may result in the model learning a sub-optimal set of weights
too fast or an unstable training process - ANSWER-The learning rate is a
hyperparameter that controls how much to change the model in response to the
estimated error each time the model weights are updated. Choosing the learning rate is
challenging. What can happen if the value is too large?
A large number of parameters comes from the dense layers at the end, and the
convolutional layers contain far fewer parameters - ANSWER-What is the proportion of
the number of parameters in the entire network while computing
A standard LSTM cell includes three gates: the forget gate to forget irrelevant
information, the input gate to remember relevant information, and the update gate to
,update new information. - ANSWER-What are the major gates in a standard LSTM
(long short-term memory) cell?
A task to be performed and a docker container to be executed - ANSWER-Kubeflow
tasks are organized into a dependency graph where each node represents
Ability to scale to a large dataset, find good features, it should be able to preprocess
with vertex AI - ANSWER-Which of the following are the requirements to build an
effective machine learning model?
Accounting and summarizing, anomaly detection, statistical analysis and clustering -
ANSWER-Components of EDA
Adding dropout layers to NN - ANSWER-How does regularization help build
generalizable models
adds the sum of the squared parameter weights term to the loss function - ANSWER-
The L2 regularization provides:
after turning your raw data into a useful feature vector - ANSWER-In what form can raw
data b used inside ML models?
An RNN uses a mechanism called hidden state to carry the previous information to the
next learning iteration. - ANSWER-What is the key feature to enable a "memory" of an
RNN (recurrent neural network)?
Analytics Hub - ANSWER-_________- efficiently and securely exchanges data analytics
assets across organizations to address challenges of data reliability and cost. You can
create and access a curated library of internal and external assets, including unique
datasets like Google Trends, backed by the power of BigQuery. There are three roles in
_____________ - A Data Publisher, Exchange Administrator, and a Data Subscriber.
Apache and TF - ANSWER-What is TensorFlow Transform a hybrid of?
Archive storage - ANSWER-Which data storage class is best for storing data that needs
to be accessed less than once a year, such as online backups and disaster recovery?
Ask the user for some basic preferences. Rely on content-based method instead for
new users - ANSWER-What are some ways you can address the cold-start problem
that can occur for new users of a collaborative filter recommendation system? There
could be more than one answer.
AutoML - ANSWER-What method do you use to create and train a model with minimal
technical effort to quickly prototype models and explore new datasets before investing in
development?
, AutoML - ANSWER-Your company has a lot of data, and you want to train your own
machine model to see what insights ML can provide. Due to resource constraints, you
require a codeless solution. Which option is best?
AutoML, which is a no-code solution, and custom training, which is a code-based
solution - ANSWER-Vertex AI provides two solutions to build an NLP project. Which of
the following is correct about these two solutions?
Avoid training server skew, avoid target leakage, provide a time signal - ANSWER-What
are the best practices for data prep?
Avoids overfitting - ANSWER-Why is regularization important in logistic regression?
Batch Load - ANSWER-Which pattern describes source data that is moved into BQ
table in a single operation?
Batch Normalization - ANSWER-_______________ applies a transformation that
maintains the mean output close to 0 and the output standard deviation close to 1
Batch serving and online serving - ANSWER-What are the two methods feature store
offers for serving features?
Big Query ML - ANSWER-For a user who can use SQL, has little Machine Learning
experience and wants a 'Low-Code' solution, which Machine Learning framework
should they use?
Both Labeled and Unlabeled data - ANSWER-Refers to the type of data used in ML
models
Both updating network weights iteratively based on training data by diagonal rescaling
of the gradients - ANSWER-how does Adam help in compiling the Keras model
BQ manages the underlying structure - ANSWER-BQ is a fully managed data
warehouse, what does fully managed refer to?
BQ ML - ANSWER-You work for a global hotel chain that has recently loaded some
guest data into BigQuery. You have experience writing SQL and want to leverage
machine learning to help predict guest trends for the next few months. Which option is
best?
By using the outputs of a component as an input of another component - ANSWER-
How can you define the pipelines workflow as a graph?
Categorical features preprocessing - ANSWER-tf.keras.layers.CategoryEncoding,
tf.keras.layers.Hashing, tf.keras.layers.IntegerLookup
