- Data Pipelines
- MLOps (Machine Learning Operations)
- Data Transformation
- Data Sharing
- Data Processing
- Data Preprocessing
- Tensorflow
- Data Management
- Performance Tuning
- Data Import/Export
- Transfer Learning
- Extract, Transform, Load
Data Pipelines with TensorFlow Data Services
Completed by Putu Indri Cahyani
November 13, 2024
11 hours (approximately)
Putu Indri Cahyani's account is verified. Coursera certifies their successful completion of Data Pipelines with TensorFlow Data Services
What you will learn
Perform efficient ETL tasks using Tensorflow Data Services APIs
Construct train/validation/test splits of any dataset - either custom or present in TensorFlow Hub Dataset library - using Splits API
Use different modules and functions of the TFDS API to prepare your data for training pipelines
Identify bottlenecks in your input pipelines and increase your workflow efficiency by input parallelization
Skills you will gain
