Data Pipelines with TensorFlow Data Services

Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this third course, you will: - Perform streamlined ETL tasks using TensorFlow Data Services - Load different datasets and custom feature vectors using TensorFlow Hub and TensorFlow Data Services APIs - Create and use pre-built pipelines for generating highly reproducible

• 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