[Coursera] TensorFlow: Data and Deployment Specialization

What you’ll learn

• Run models in your browser using TensorFlow.js

• Prepare and deploy models on mobile devices using TensorFlow Lite

• Access, organize, and process training data more easily using TensorFlow Data Services

• Explore four advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, and TensorBoard


Skills you’ll gain

• Tensorflow
• Object Detection
• Machine Learning
• JavaScript
• Advanced deployment


Specialization – 4 course series

Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.

In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data, and retrain deployed models with user data while maintaining data privacy.   Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more.

Industries all around the world are adopting Artificial Intelligence. This Specialization from Laurence Moroney and Andrew Ng will help you develop and deploy machine learning models across any device or platform faster and more accurately than ever.

1. Browser-based Models with TensorFlow.js
2. Device-based Models with TensorFlow Lite
3. Data Pipelines with TensorFlow Data Services
4. Advanced Deployment Scenarios with TensorFlow

4 Courses, Total, 752 Files, 110 Folders


Applied Learning Project

In the TensorFlow: Data and Deployment Specialization, you will learn to apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more, implementing projects you can add to your portfolio and show in interviews.



Laurence Moroney, leads AI Advocacy at Google, with a vision to make AI easy for developers and to widen access to ML careers for everyone. He’s written dozens of programming books, the most recent being ‘AI and ML for Coders’ at O’Reilly. Laurence believes that MOOCs are one of the greatest ways to learn, and is excited to create TensorFlow Specializations with DeepLearning.AI on Coursera. When not working with technology, he’s an active member of the Science Fiction Writers of America, and has authored several sci-fi novels, and comics books, and a produced screenplay. Laurence is based in Washington state, where he drinks way too much coffee.

Offered By DeepLearning.AI


Media Information:

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.100 KHz, 2 Ch
Genre: eLearning | Language: English + SRT | Updated: 3/2024 | Duration: 208 Lessons ( 7h 56m 15s )

Source: https://www.coursera.org/specializations/tensorflow-data-and-deployment


Size: 1.35GB

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