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.
This course is part of the TensorFlow: Data and Deployment Specialization
Offered By


About this Course
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
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
- Artificial Neural Network
- Tensorflow
- Extraction, Transformation And Loading (ETL)
- Data Pipelines
- TensorFlow Datasets
We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have a basic familiarity with building models in TensorFlow
Offered by
Syllabus - What you will learn from this course
Data Pipelines with TensorFlow Data Services
Splits and Slices API for Datasets in TF
Exporting Your Data into the Training Pipeline
Performance
Reviews
- 5 stars64.64%
- 4 stars19.73%
- 3 stars8.89%
- 2 stars4.12%
- 1 star2.60%
TOP REVIEWS FROM DATA PIPELINES WITH TENSORFLOW DATA SERVICES
First 3 weeks are really nice but for me week 4 was a bit tough with very less explanation
I was really looking forward to learning efficient data pipelines and that is utterly what I learned here in this course. Best in its class.
Laurence cares deeply about the students. Not only about what they learn, but that they actually enjoy and learn it. What a fantastic teacher.
This course many for challengging in code but, before it, i learn it in my college. So, i do this assignment.
About the TensorFlow: Data and Deployment Specialization

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Why was Course 3: Data Pipelines with TensorFlow Data Service updated in October 2020?
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