Data Pipelines with TensorFlow Data Services
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Data Pipelines with TensorFlow Data Services
This course is part of TensorFlow: Data and Deployment Specialization
Instructor: Laurence Moroney
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What you'll 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'll gain
Tools you'll learn
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There are 4 modules in this course
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 I/O pipelines for any dataset - Optimize data pipelines that become a bottleneck in the training process - Publish your own datasets to the TensorFlow Hub library and share standardized data with researchers and developers around the world This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.
This week, you will be able to perform efficient ETL tasks using Tensorflow Data Services APIs
What's included
10 videos6 readings1 assignment1 programming assignment
10 videos•Total 21 minutes
- A conversation with Andrew Ng•2 minutes
- Introduction•1 minute
- Popular Datasets•3 minutes
- Data Pipelines•1 minute
- Extract, Transform and Load•3 minutes
- Versioning Datasets•3 minutes
- Looking at the Notebook•2 minutes
- Using TFDS in Keras to Train Fashion MNIST •3 minutes
- Horses or Humans in TFDS•3 minutes
- Week 1 Wrap Up•1 minute
6 readings•Total 43 minutes
- Downloading the Ungraded Labs and Programming Assignments•10 minutes
- Join the DeepLearning.AI Forum to ask questions, get support, or share amazing ideas!•2 minutes
- Try Out the Notebook Yourself•10 minutes
- Try the Horses or Human Notebook•10 minutes
- Lecture Notes Week 1•1 minute
- Grader Note•10 minutes
1 assignment•Total 30 minutes
- Week 1 Quiz•30 minutes
1 programming assignment•Total 60 minutes
- TFDS with Rock, Paper and Scissors•60 minutes
In this week, you will construct train/validation/test splits of any dataset - either custom or present in TensorFlow hub dataset library - using Splits API
What's included
7 videos4 readings1 assignment1 programming assignment
7 videos•Total 26 minutes
- Introduction•2 minutes
- Introduction to Splits API•5 minutes
- Splits API Notebook Walkthrough•5 minutes
- File Structure in TensorFlow Datasets•2 minutes
- Feature Descriptors•5 minutes
- TFRecord Colab Walkthrough•6 minutes
- Week 2 Wrap Up•1 minute
4 readings•Total 31 minutes
- Splits API Notebook•10 minutes
- TFRecord Notebook •10 minutes
- Lecture Notes Week 2•1 minute
- Grader Note•10 minutes
1 assignment•Total 30 minutes
- Week 2•30 minutes
1 programming assignment•Total 60 minutes
- Transfer Learning and Splits API•60 minutes
This week you will extend your knowledge of data pipelines
What's included
21 videos6 readings1 assignment1 programming assignment
21 videos•Total 44 minutes
- A Conversation with Andrew Ng•1 minute
- Introduction•0 minutes
- Input Data•1 minute
- Basic Mechanics•3 minutes
- Numeric and Bucketized Columns•2 minutes
- Vocabulary and Hashed Columns, Feature Crossing•2 minutes
- Embedding Columns•2 minutes
- Introduction•0 minutes
- Notebook Walkthrough•4 minutes
- Introduction•0 minutes
- Numpy, Pandas and Images•3 minutes
- CSV•4 minutes
- Text and TFRecord•1 minute
- Generators•1 minute
- Introduction•0 minutes
- Notebook walkthrough•5 minutes
- Introduction•1 minute
- Using Numpy and Pandas•2 minutes
- Image Data•1 minute
- CSV Data•4 minutes
- Text Data•3 minutes
6 readings•Total 51 minutes
- Link to the Notebook•10 minutes
- Link to the CNN Course•10 minutes
- Link to the Notebook•10 minutes
- CSV Notebook•10 minutes
- Link to the Course •10 minutes
- Lecture Notes Week 3•1 minute
1 assignment•Total 30 minutes
- Week 3 Quiz•30 minutes
1 programming assignment•Total 60 minutes
- Classify Structured Data•60 minutes
You'll learn how to handle your data input to avoid bottlenecks, race conditions and more!
What's included
22 videos4 readings2 assignments1 programming assignment1 ungraded lab
22 videos•Total 44 minutes
- A conversation with Andrew Ng•2 minutes
- Introduction•1 minute
- ETL•2 minutes
- What Happens When You Train a Model•3 minutes
- Introduction•0 minutes
- Caching•1 minute
- Parallelism APIs•2 minutes
- Autotuning•2 minutes
- Parallelizing Data Extraction•2 minutes
- Best Practices for Code Improvements•3 minutes
- A Few Words by Laurence•1 minute
- A conversation with Andrew Ng•1 minute
- Introduction•1 minute
- How to Start Using a Dataset•3 minutes
- Implementation•4 minutes
- File Access and Possible Problems in Data•4 minutes
- Publishing the Dataset•4 minutes
- Introduction•0 minutes
- Going Through the Colab- Part 1•2 minutes
- Going Through the Colab - Part 2•3 minutes
- Closing Words•0 minutes
- A conversation with Andrew Ng•2 minutes
4 readings•Total 23 minutes
- Lecture Notes Week 4•1 minute
- [IMPORTANT] Reminder about end of access to Lab Notebooks•2 minutes
- URLs•10 minutes
- Link to the Colab•10 minutes
2 assignments
- Week 4 Quiz•0 minutes
- Publishing your Dataset Quiz•0 minutes
1 programming assignment•Total 60 minutes
- Parallelization with TFDS•60 minutes
1 ungraded lab•Total 60 minutes
- Adding a Dataset of your Own to TFDS•60 minutes
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Reviewed on Feb 2, 2021
Great explanation, however I believe in Week3 there are some broken links . . .heart.csv
Reviewed on Oct 2, 2020
Just what i needed. Would have gotten 5 starts, if they fix the last lab.
Reviewed on Jul 7, 2020
First 3 weeks are really nice but for me week 4 was a bit tough with very less explanation
Frequently asked questions
Changes in TensorFlow API: Since this Specialization was launched in early 2020, there have been changes to the TensorFlow API which affect the material in Weeks 1 and 2. With this refresh, you can access updated lectures, quizzes, and assignments.
Changing the Difficulty Level of Assignments: Based on valuable learner feedback, we’ve revised the Week 4 assignments to ensure that you have a full grasp of the foundational principles and are well-prepared to tackle them.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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Financial aid available,