DeepLearning.AI - Advanced Deployment Scenarios with TensorFlow
- Offered byCoursera
Advanced Deployment Scenarios with TensorFlow at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Advanced Deployment Scenarios with TensorFlow at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 4 of 4 in the TensorFlow: Data and Deployment Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level We recommend taking Course 1 of the TensorFlow in Practice Specialization first, or have basic familiarity with building models in TensorFlow.
- Approx. 13 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Advanced Deployment Scenarios with TensorFlow at Coursera Course details
- 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 final course, you?ll explore four different scenarios you?ll encounter when deploying models. You?ll be introduced to TensorFlow Serving, a technology that lets you do inference over the web. You?ll move on to TensorFlow Hub, a repository of models that you can use for transfer learning. Then you?ll use TensorBoard to evaluate and understand how your models work, as well as share your model metadata with others. Finally, you?ll explore federated learning and how you can retrain deployed models with user data while maintaining data privacy.
- 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.
Advanced Deployment Scenarios with TensorFlow at Coursera Curriculum
TensorFlow Extended
Introduction, A conversation with Andrew Ng
Introduction
Serving
Installing TF Serving
TensorFlow Serving summary
Setup for serving
Serving
Predictions
Passing data to serving
Getting the predictions back
Running the colab
Complex model
Downloading the Coding Examples and Exercises
Installation link
TF server running in colab
Serving with Fashion MNIST
Ungraded Exercise - Serving with MNIST
Week 1 Quiz
Sharing pre-trained models with TensorFlow Hub
Introduction, A conversation with Andrew Ng
Introduction to TF Hub
Transfer learning
Inference
Module storage
Text based models
Word embeddings
Experimenting with embeddings
Colab
Classify cats and dogs
Transfer learning
Tensorflow Hub link
Link to saved models
Colab
Pre-trained Word Embeddings
Text Classification Colab
MobileNet model details
Colab
Week 2 Quiz
Tensorboard: tools for model training
Introduction, A conversation with Andrew Ng
Tensorboard scalars
Callbacks
Histograms
Publishing model details
Local tensorboard
Looking at graphics in a dataset
More than one image
Confusion matrix
Multiple callbacks
tensorboard.dev
Colab
Week 3 Quiz
Federated Learning
Introduction, A conversation with Andrew Ng
Training on mobile devices
Data at the edge
How it works
Maintaining user privacy
Masking
APIs for Federated Learning
Example of federated learning
Outro
Colab
What next?
Week 4 Quiz
Advanced Deployment Scenarios with TensorFlow at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
Anything you would want to ask experts?