Description for Getting Started with BigQuery ML
BigQuery Machine Learning Model Creation: Acquire the ability to generate machine learning models in BigQuery that generate predictions based on structured datasets.
Methods of Assessment: Acquire an understanding of the techniques used to assess the accuracy and efficacy of models in BigQuery.
Application of Predictive Analytics: Develop a model that can predict the likelihood of a transaction, thereby facilitating practical implementations in the field of visitor behavior analytics.
Google Cloud Console: Experience A fundamental comprehension of BigQuery's machine learning capabilities is achieved through practical experience with the Google Cloud console.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 45 minutes at your own pace
Schedule: Hands-on learning
Pricing for Getting Started with BigQuery ML
Use Cases for Getting Started with BigQuery ML
FAQs for Getting Started with BigQuery ML
Reviews for Getting Started with BigQuery ML
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Getting Started with BigQuery ML
Featured Tools
In less than six months, acquire skills that are in high demand, including machine learning, regression models, Python, and statistical analysis.
Acquire a basic understanding of digital transformation and cloud computing. Boost your cloud confidence to enable you to engage in discussions with colleagues in technical cloud positions and make informed business decisions regarding cloud technology.
Learn to describe and implement various machine learning algorithms in Python, including classification and regression techniques, and evaluate their performance using appropriate metrics.
Gain practical skills to implement models in Python across diverse industries while exploring machine learning and deep learning concepts.
Gain the skills needed for a machine learning engineering role and prepare for the Google Cloud Professional Machine Learning Engineer certification exam by learning to design, build, and productize ML models using Google Cloud technologies.