DeepLearning.AI
TensorFlow: Data and Deployment Specialization
DeepLearning.AI

TensorFlow: Data and Deployment Specialization

Taught in English

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Laurence Moroney

Instructor: Laurence Moroney

37,350 already enrolled

Specialization - 4 course series

Get in-depth knowledge of a subject

4.7

(1,343 reviews)

Intermediate level
Some related experience required
1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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

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Specialization - 4 course series

Get in-depth knowledge of a subject

4.7

(1,343 reviews)

Intermediate level
Some related experience required
1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 4 course series

Browser-based Models with TensorFlow.js

Course 118 hours4.8 (982 ratings)

What you'll learn

  • Train and run inference in a browser

  • Handle data in a browser

  • Build an object classification and recognition model using a webcam

Skills you'll gain

Category: Tensorflow
Category: Convolutional Neural Network
Category: Object Detection
Category: Machine Learning
Category: TensorFlow.js

Device-based Models with TensorFlow Lite

Course 210 hours4.7 (633 ratings)

What you'll learn

  • Prepare models for battery-operated devices

  • Execute models on Android and iOS platforms

  • Deploy models on embedded systems like Raspberry Pi and microcontrollers

Skills you'll gain

Category: Tensorflow
Category: Object Detection
Category: Machine Learning
Category: Mathematical Optimization
Category: TensorFlow Lite

Data Pipelines with TensorFlow Data Services

Course 311 hours4.4 (512 ratings)

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

Category: Tensorflow
Category: Extraction, Transformation And Loading (ETL)
Category: Artificial Neural Network
Category: TensorFlow Datasets
Category: Data Pipelines

Advanced Deployment Scenarios with TensorFlow

Course 412 hours4.8 (500 ratings)

What you'll learn

  • Use TensorFlow Serving to do inference over the web

  • Navigate TensorFlow Hub, a repository of models that you can use for transfer learning

  • Evaluate how your models work and share model metadata using TensorBoard

  • Explore federated learning and how to retrain deployed models while maintaining data privacy

Skills you'll gain

Category: Machine Learning
Category: TensorBoard
Category: federated learning
Category: TensorFlow Serving
Category: TensorFlow Hub

Instructor

Laurence Moroney
DeepLearning.AI
15 Courses495,705 learners

Offered by

DeepLearning.AI

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