Smart Analytics, Machine Learning, and AI on Google Cloud
Skills:
ML Pipelines80%
Key Takeaways
Utilizes AutoML, Notebooks, and BigQuery machine learning on Google Cloud for data pipelines
Original Description
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: ML Pipelines
View skill →Related Reads
📰
📰
📰
📰
I Built My Second ETL Pipeline. This Time, I Started Thinking Like a Data Engineer
Towards Data Science
JuiceFS Sync for PB-Scale Data Transfers: Resumable Sync, Encryption, and Bandwidth Control
Dev.to AI
How Airflow is using AI to make data engineering more resilient, not more complex
Medium · AI
What Can We Do When Memory Becomes the New Bottleneck in Data Engineering?
Towards Data Science
🎓
Tutor Explanation
DeepCamp AI