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Learner Reviews & Feedback for Getting started with TensorFlow 2 by Imperial College London

4.9
stars
568 ratings

About the Course

Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills. At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop an image classifier deep learning model from scratch. Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning. The release of Tensorflow 2 marks a step change in the product development, with a central focus on ease of use for all users, from beginner to advanced level. This course is intended for both users who are completely new to Tensorflow, as well as users with experience in Tensorflow 1.x. The prerequisite knowledge required in order to be successful in this course is proficiency in the python programming language, (this course uses python 3), knowledge of general machine learning concepts (such as overfitting/underfitting, supervised learning tasks, validation, regularisation and model selection), and a working knowledge of the field of deep learning, including typical model architectures (MLP/feedforward and convolutional neural networks), activation functions, output layers, and optimisation....

Top reviews

MM

Jan 24, 2021

I already knew the subject, so I was able to go fast, but I really loved the completeness of this course, the approach, the tests, and the capstone project. Basically everything. Very good indeed!

AJ

Sep 9, 2020

Excellent course with thorough practical exercises and most of all I love Kevin Webster teaching style.. Definitely a go to course for anyone who has some basic Deep Learning knowlegde.

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151 - 175 of 184 Reviews for Getting started with TensorFlow 2

By Zhongtian Y

•

Sep 23, 2020

Easy to understand! Nice course!

By Vassil

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Aug 26, 2022

Very good learning experiene!

By José P

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Apr 18, 2021

Nice course, thank you all!

By Ragul N

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Nov 23, 2020

Best course on Tensorflow 2

By akshaykiranjose

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Jun 6, 2022

thanks, guys at imperial

By Dai T

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Sep 21, 2020

Best Tensorflow Course!

By Hugo R V A

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Sep 16, 2021

Just amazing! Perfect!

By Duc A L

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Feb 19, 2021

Good course to learn

By Mohammed A K

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Jan 25, 2022

outstanding course!

By Айрапетян Ж С

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Jan 28, 2021

Great intro to tf2.

By MoChuxian

•

Oct 27, 2020

very nice course!!!

By Alireza K

•

Aug 17, 2023

very good progects

By Nguyen T S

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Jan 24, 2022

Excellent course!

By Gustavo X A M

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Nov 18, 2020

Excellent course

By Wong H S

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Nov 2, 2020

Awesome content!

By Peter W

•

Feb 24, 2021

great course!

By Yuzhe D

•

Dec 28, 2020

Great course

By Syed H M

•

May 29, 2024

Good course

By Engr. M S K

•

Mar 7, 2022

Best Course

By Adam H

•

Nov 29, 2022

Amazing!

By Meng O L

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Oct 27, 2020

Awesome

By Fayas A

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Jun 18, 2023

great

By Kellen X

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Dec 11, 2020

Great

By Yukihiro F

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Nov 1, 2023

First of all, this course is not a deep learning course but a TensorFlow2 course, so prior knowledge of deep learning is required. For example, if you don't understand what CNN (Convolutional Neural Network) is, it's recommended to take a dedicated deep learning course, such as OpenAI's, before starting this course. With that in mind, the content of this course is excellent. You will become proficient in executing what you imagine using TensorFlow2. However, there are some drawbacks. Almost every module consists of the following components: 1. Videos where the instructor explains concepts while showing code. 2. Videos where the TA (Teaching Assistant) explains concepts while coding. 3. JupyterNotebook exercises. 1 and 2 are quite redundant. Moreover, video 2 involves typing out code from scratch instead of explaining pre-written code, which makes the videos unnecessarily long. Typing out code while watching the video was quite painful. In addition, the lab's automatic grading tool was a bit unstable. Particularly, during the second week's auto-grading, it would fail when the lab was working correctly, and pass when errors occurred while coding as per the instructions on the lab. Additionally, there were issues with the peer review assignment, as attempting to generate a PDF as instructed resulted in a server-side error, preventing the output. I downloaded the Jupyter project and struggled to generate a PDF from my local JupyterLab.

By J H v d M

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Apr 24, 2021

If it were not for the difficulties encountered with using some of the online Labs, esp. the Capstone project, would have been 5 stars (which I rarely give).

I had to resort to using my own 2016 vintage Asus laptop w. 1070 GPU to get the Capstone going; the Lab totally gummed up.

All in all excellent course also as refresher. On to completing the next two now.

Thanks a lot, Jan van de Mortel