BigQuery

Question 1

Is Logistic Regression built-in to BigQuery or externally trained in Vertex AI?

Answer 1

Built in to BigQuery

Question 2

What is AutoML used for?

Answer 2

supervised ML service that builds and deploys classification and regression models on tabular data at high speed and scale.

Question 3

What is Deep neural network used for?

Answer 3

creating TensorFlow-based deep neural networks for classification and regression models.

Question 4

Is Random forest built-in to BigQuery or externally trained in Vertex AI?

Answer 4

Trained in Vertex AI

Question 5

What is K-means clustering used for?

Answer 5

data segmentation. For example, this model identifies customer segments. K-means is an unsupervised learning technique, so model training doesn’t require labels or split data for training or evaluation.

Question 6

Is Boosted Tree built-in to BigQuery or externally trained in Vertex AI?

Answer 6

Trained in Vertex AI

Question 7

What is Boosted Tree used for?

Answer 7

creating classification and regression models that are based on XGBoost.

Question 8

Is Contribution Analysis built-in to BigQuery or externally trained in Vertex AI?

Answer 8

Built in to BigQuery

Question 9

What is Random forest used for?

Answer 9

constructing multiple learning method decision trees for classification, regression, and other tasks at training time.

Question 10

What is Principal component analysis (PCA) used for?

Answer 10

the process of computing the principal components and using them to perform a change of basis on the data. It’s commonly used for dimensionality reduction by projecting each data point onto only the first few principal components to obtain lower-dimensional data while preserving as much of the data’s variation as possible.

Question 11

What is Time series used for?

Answer 11

performing time series forecasts. You can use this feature to create millions of time series models and use them for forecasting. The model automatically handles anomalies, seasonality, and holidays.

Question 12

Is Autoencoder built-in to BigQuery or externally trained in Vertex AI?

Answer 12

Trained in Vertex AI

Question 13

Is Time Series built-in to BigQuery or externally trained in Vertex AI?

Answer 13

Built in to BigQuery

Question 14

What is Linear regression used for?

Answer 14

Predicting the value of a numerical metric for new data by using a model trained on similar remote data. Labels are real-valued, meaning they cannot be positive infinity or negative infinity or a NaN.

Question 15

Is Wide & Deep built-in to BigQuery or externally trained in Vertex AI?

Answer 15

Trained in Vertex AI

Question 16

Is AutoML built-in to BigQuery or externally trained in Vertex AI?

Answer 16

Trained in Vertex AI

Question 17

Language used in BigQuery

Answer 17

SQL

Question 18

Is Linear Regression built-in to BigQuery or externally trained in Vertex AI?

Answer 18

Built in to BigQuery

Question 19

Is Deep neural network (DNN) built-in to BigQuery or externally trained in Vertex AI?

Answer 19

Trained in Vertex AI

Question 20

What is Autoencoder used for?

Answer 20

creating TensorFlow-based models with the support of sparse data representations. You can use the models in BigQuery ML for tasks such as unsupervised anomaly detection and non-linear dimensionality reduction.

Question 21

What is Logistic regression used for?

Answer 21

the classification of two or more possible values such as whether an input is low-value, medium-value, or high-value. Labels can have up to 50 unique values.

Question 22

What is Contribution Analysis used for?

Answer 22

Determining the effect of one or more dimensions on the value for a given metric. For example, seeing the effect of store location and sales date on store revenue.

Question 23

Is Matrix Factorisation built-in to BigQuery or externally trained in Vertex AI?

Answer 23

Built in to BigQuery

Question 24

What is Matrix factorization used for?

Answer 24

creating product recommendation systems. You can create product recommendations using historical customer behavior, transactions, and product ratings, and then use those recommendations for personalized customer experiences.

Question 25

Do you need to move and format data for Python-based ML frameworks?

Answer 25

No, BigQuery brings ML to the Data, in the SQL database.

Question 26

Is K-means Clustering built-in to BigQuery or externally trained in Vertex AI?

Answer 26

Built in to BigQuery

Question 27

Is Principal Component Analysis built-in to BigQuery or externally trained in Vertex AI?

Answer 27

Built in to BigQuery

Question 28

What is Wide & Deep used for?

Answer 28

generic large-scale regression and classification problems with sparse inputs (categorical features with a large number of possible feature values), such as recommender systems, search, and ranking problems.

Question 29

Feature Selection and Engineering can be done using what keyword?

Answer 29

TRANSFORM

Question 30

What can the TRANSFORM clause do?

Answer 30

Feature selection AND feature engineering