Mydra logo
Log in
>All courses>Artificial Intelligence
Artificial Intelligence
DeepLearning.AI logo

DeepLearning.AI

TensorFlow: Data and Deployment Specialization

  • up to 4 months
  • Intermediate

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.

  • Machine Learning
  • TensorFlow
  • Advanced Deployment
  • Object Detection
  • JavaScript

Overview

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.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Professional Certification
    upon course completion
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Machine Learning Engineers

Professionals looking to deploy machine learning models on various platforms.

Data Scientists

Individuals aiming to enhance their skills in data processing and model deployment.

Software Developers

Developers interested in integrating machine learning models into their applications.

This course will help you deploy machine learning models on various platforms, enhancing your skills in data processing and model deployment. Ideal for machine learning engineers, data scientists, and software developers, this course will advance your career by providing practical knowledge and hands-on experience.

Pre-Requisites

1 / 3

  • Basic understanding of machine learning concepts

  • Familiarity with TensorFlow

  • Experience with programming in Python

What will you learn?

Course 1: Browser-based Models with TensorFlow.js
Learn how to train and run machine learning models in any browser using TensorFlow.js. Techniques for handling data in the browser and building a computer vision project that recognizes and classifies objects from a webcam.
Course 2: Device-based Models with TensorFlow Lite
Run your machine learning models in mobile applications. Prepare models for lower-powered, battery-operated devices, and deploy on Android, iOS, and embedded systems using TensorFlow on Raspberry Pi and microcontrollers.
Course 3: Data Pipelines with TensorFlow Data Services
Perform efficient ETL tasks using TensorFlow Data Services APIs. Construct train/validation/test splits of any dataset and prepare your data for training pipelines. Identify bottlenecks in your input pipelines and increase workflow efficiency.
Course 4: Advanced Deployment Scenarios with TensorFlow
Explore four different scenarios for deploying models. Learn about TensorFlow Serving, TensorFlow Hub, TensorBoard, and federated learning to retrain deployed models with user data while maintaining data privacy.

Meet your instructor

  • Laurence Moroney

    Award-winning AI Researcher | Best Selling Author | Fellow at the AI Fund | Advisor to many | Inspiring the world about AI, DeepLearning.AI

    For over 10 years, Laurence Moroney has served as an AI Lead at Google, driving the corporate-wide narrative for developers on the possibilities of AI and ML. He has worn many hats throughout his career, including researcher, developer, educator, and author.

Upcoming cohorts

  • Dates

    start now

$49