Imperial College London

Getting started with TensorFlow 2

Dr Kevin Webster

Instructor: Dr Kevin Webster

37,172 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.9

(569 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 26 hours
Learn at your own pace
96%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.9

(569 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 26 hours
Learn at your own pace
96%
Most learners liked this course

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Placeholder

Build your subject-matter expertise

This course is part of the TensorFlow 2 for Deep Learning Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 5 modules in this course

TensorFlow is one of the most popular libraries for deep learning, and it’s widely used today amongst researchers and professionals at all levels. In this week, you will get started with using TensorFlow on the Coursera platform and familiarise yourself with the course structure. You will also learn about some helpful resources when developing deep learning models in TensorFlow, including Google Colab. This week is really about getting everything set up, ready for diving into TensorFlow in the following week of the course.

What's included

14 videos8 readings1 discussion prompt1 ungraded lab1 plugin

There are multiple ways to build and apply deep learning models in TensorFlow, from high-level, quick and easy-to-use APIs, to low-level operations. In this week you will learn to use the high-level Keras API for quickly building, training, evaluating and predicting from deep learning models. The programming assignment for this week will give you the opportunity to put all this into practice and develop an image classification model from scratch on the MNIST dataset of handwritten images.

What's included

13 videos2 assignments1 programming assignment8 ungraded labs

Model validation and selection is an essential part of developing any machine learning model development to help prevent overfitting and improve generalisation. In this week you will learn how to use a validation dataset in a training run and apply regularisation techniques to your model. You will also learn how to use callbacks to monitor performance and perform actions according to specified criteria. In the programming assignment for this week you will put model validation and regularisation into practice on the well-known Iris dataset.

What's included

11 videos1 assignment1 programming assignment8 ungraded labs

As part of your deep learning model development, you will need to be able to save and load TensorFlow models, possibly according to certain criteria you want to specify. In this week you will learn how to use callbacks to save models, manual saving and loading, and options that are available when saving models, including saving weights only. In addition, you will practice loading and using pre-trained deep learning models. In the programming assignment for this week you will write flexible model saving and loading implementations for a model trained on satellite images.

What's included

12 videos1 programming assignment8 ungraded labs

In this course you have learned an end-to-end workflow for developing deep learning models in Tensorflow. The Capstone Project gives you the opportunity to bring all of your knowledge together to develop a deep learning classifier on a labelled image dataset of street view house numbers.

What's included

2 videos1 peer review1 ungraded lab1 plugin

Instructor

Instructor ratings
4.9 (179 ratings)
Dr Kevin Webster
Imperial College London
6 Courses45,055 learners

Offered by

Recommended if you're interested in Machine Learning

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

4.9

569 reviews

  • 5 stars

    91.03%

  • 4 stars

    7.38%

  • 3 stars

    0.52%

  • 2 stars

    0.17%

  • 1 star

    0.87%

Showing 3 of 569

AJ
5

Reviewed on Sep 9, 2020

AA
5

Reviewed on Mar 17, 2021

DJ
4

Reviewed on Aug 18, 2020

New to Machine Learning? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions