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Getting started with TensorFlow 2 に戻る

インペリアル・カレッジ・ロンドン(Imperial College London) による Getting started with TensorFlow 2 の受講者のレビューおよびフィードバック



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....




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!



Provided clear and useful insight into TensorFlow 2. Before the course I had read many of the TF2 guides and tutorials. This course helped solidify my understanding of core TF concepts.


Getting started with TensorFlow 2: 126 - 150 / 157 レビュー

by Bhasker D


Excellent Course, Thank you Kevin

by Mike M


Just what the ML doctor ordered.

by fan c


Very good. Basic but Systematic.

by Zhongtian Y


Easy to understand! Nice course!

by José P


Nice course, thank you all!

by Ragul N


Best course on Tensorflow 2

by akshaykiranjose


thanks, guys at imperial

by Dai Q T


Best Tensorflow Course!

by Hugo R V A


Just amazing! Perfect!

by Duc A L


Good course to learn

by Mohammed A


outstanding course!

by Айрапетян Ж С


Great intro to tf2.

by MoChuxian


very nice course!!!

by Nguyen T S


Excellent course!

by Gustavo X A M


Excellent course

by Wong H S


Awesome content!

by Huang P


great course!

by Yuzhe D


Great course

by Engr. M S K


Best Course

by Meng O L



by Zikun X



by J H v d M


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

by mgbacher


The course is a good introduction to applicable deep learning using Keras. Do not expect any mathematical derivations. These you would need to gather from other courses such as I enjoyed the quizzes. The capstone project could be made more challenging by exploiting different aspects of layers, benchmarking pre-trained networks, and training strategies.

by Christian C


For me, the course lived up to its name. It was not too theory-focused, and focused really on getting started with TensorFlow 2. The programming exercises, which use different well-known datasets, are designed just enough to not feel being spoon-fed. The peer-reviewed capstone project is also a great experience.

by Daniel H


A clearly organized and presented course. The capstone project may be a bit challenging because you will need to recall what you learned and apply it to what you may already know or need to go research. It's worth the effort.