Statements (69)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:machine_learning
gptkb:Data_Analytics |
| gptkbp:allows |
hyperparameter tuning
machine learning models to be created and executed in Big Query |
| gptkbp:can_be_used_for |
financial forecasting
predictive analytics classification tasks text analysis customer segmentation recommendation systems healthcare analytics anomaly detection image analysis regression tasks marketing analytics |
| gptkbp:can_handle |
large datasets
|
| gptkbp:developed_by |
gptkb:Google_Cloud
|
| gptkbp:enables |
model evaluation and validation
|
| gptkbp:facilitates |
collaborative data science
|
| https://www.w3.org/2000/01/rdf-schema#label |
Big Query ML
|
| gptkbp:integrates_with |
gptkb:Microsoft_Excel
gptkb:Data Big Query data warehouse |
| gptkbp:is_accessible_by |
gptkb:Big_Query_API
non-programmers Big Query console |
| gptkbp:is_available_in |
multiple regions globally
|
| gptkbp:is_based_on |
Google's Tensor Flow technology
|
| gptkbp:is_compatible_with |
gptkb:Jupyter_notebooks
|
| gptkbp:is_designed_for |
data analysts and data scientists
|
| gptkbp:is_designed_to |
simplify machine learning processes
|
| gptkbp:is_known_for |
ease of use
cost-effectiveness |
| gptkbp:is_part_of |
gptkb:Google_Cloud_Platform
data analytics solutions Google's AI and machine learning ecosystem Google's cloud-native tools data democratization efforts. |
| gptkbp:is_recognized_for |
speed and efficiency
|
| gptkbp:is_scalable |
petabyte-scale data
|
| gptkbp:is_supported_by |
Google Cloud documentation
|
| gptkbp:is_updated_by |
new features regularly
|
| gptkbp:is_used_by |
businesses and organizations
|
| gptkbp:is_used_for |
supply chain optimization
social media analytics e-commerce analytics |
| gptkbp:is_used_in |
data-driven decision making
real-time analytics data science competitions |
| gptkbp:is_utilized_by |
startups and enterprises alike
|
| gptkbp:offers |
linear regression models
k-means clustering models logistic regression models time series forecasting models |
| gptkbp:provides |
model explainability features
data visualization capabilities automated machine learning capabilities automated feature engineering model training options |
| gptkbp:suitable_for |
business intelligence applications
|
| gptkbp:supports |
multiple programming languages
user-defined functions batch predictions online predictions SQL syntax for model training |
| gptkbp:uses |
Big Query SQL for data manipulation
|
| gptkbp:bfsParent |
gptkb:Google_AI
gptkb:Google_Cloud_AI |
| gptkbp:bfsLayer |
5
|