Buy Now AED 170.99 + VAT

Monthly Subscription Starting at AED 99 + VAT

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  • Level Professional
  • Duration 18 hours
  • Course by DeepLearning.AI
  • Offered by

About

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

Modules

A new programming paradigm

    • 4 Videos
    • 4 Readings
    • 1 ExternalTool
    • 1 Plugin
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 1 Quiz

1 External Tool

  • Intake Survey

1 Labs

  • Try it for yourself (Lab 1)

4 Videos

  • Introduction: A conversation with Andrew Ng
  • A primer in machine learning
  • The ‘Hello World’ of neural networks
  • Working through ‘Hello World’ in TensorFlow and Python

4 Readings

  • Welcome to the course!
  • [IMPORTANT] Have questions, issues or ideas? Join our Forum!
  • From rules to data
  • About the notebooks in this course

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 1

Weekly Assignment - Your First Neural Network

    • 3 Readings
    • 1 Programming
Show info about module content

1 Programming

  • Housing Prices

3 Readings

  • Assignment Troubleshooting Tips
  • (Optional) Downloading your Notebook and Refreshing your Workspace
  • Week 1 Resources

Introduction to Computer Vision

    • 7 Videos
    • 2 Readings
    • 2 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 2 Quiz

2 Labs

  • Get hands-on with computer vision (Lab 1)
  • See how to implement Callbacks (Lab 2)

7 Videos

  • A Conversation with Andrew Ng
  • An Introduction to computer vision
  • Writing code to load training data
  • Coding a Computer Vision Neural Network
  • Walk through a Notebook for computer vision
  • Using Callbacks to control training
  • Walk through a notebook with Callbacks

2 Readings

  • Exploring how to use data
  • Labelling the Fashion MNIST data

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 2

Weekly Assignment - Implement a Deep Neural Network to recognize handwritten digits

    • 1 Programming
Show info about module content

1 Programming

  • Implementing Callbacks in TensorFlow using the MNIST Dataset

Enhancing Vision with Convolutional Neural Networks

    • 6 Videos
    • 2 Readings
    • 2 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 3 Quiz

2 Labs

  • Try it for yourself (Lab 1)
  • Experiment with filters and pools (Lab 2)

6 Videos

  • A conversation with Andrew Ng
  • What are convolutions and pooling?
  • Implementing convolutional layers
  • Implementing pooling layers
  • Improving the Fashion classifier with convolutions
  • Walking through convolutions

2 Readings

  • Coding convolutions and pooling layers
  • Learn more about convolutions

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 3

Weekly Assignment - Improving DNN Performance using Convolutions

    • 1 Programming
Show info about module content

1 Programming

  • Improve MNIST with convolutions

Using Real-world Images

    • 8 Videos
    • 2 Readings
    • 3 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Week 4 Quiz

3 Labs

  • Experiment with the horse or human classifier (Lab 1)
  • Get hands-on and use validation (Lab 2)
  • Get hands-on with compacted images (Lab 3)

8 Videos

  • A conversation with Andrew Ng
  • Understanding the tf.data API
  • Defining a ConvNet to use complex images
  • Training the ConvNet
  • Walking through developing a ConvNet
  • Walking through training the ConvNet
  • Adding automatic validation to test accuracy
  • Exploring the impact of compressing images

2 Readings

  • Explore an impactful, real-world solution
  • Training the neural network

Lecture Notes (Optional)

    • 1 Readings
Show info about module content

1 Readings

  • Lecture Notes Week 4

End of Access to Lab Notebooks

    • 1 Readings
Show info about module content

1 Readings

  • [IMPORTANT] Reminder about end of access to Lab Notebooks

Weekly Assignment - Handling Complex Images

    • 1 Programming
Show info about module content

1 Programming

  • Handling Complex Images

Course 1 Wrap up

    • 1 Videos
    • 1 Readings
Show info about module content

1 Videos

  • A conversation with Andrew

1 Readings

  • Wrap up

Acknowledgments

    • 1 Readings
Show info about module content

1 Readings

  • Acknowledgments
Laurence Moroney
Instructor

Laurence Moroney