Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.In this four-course Specialization, you'll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network's performance using convolutions as you train it to identify real-world images. You'll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input

Created by: Laurence Moroney

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Overall Score : 98 / 100

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Course Description

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 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.

Instructor Details

Laurence Moroney

Laurence Moroney is a Developer Advocate at Google working on Artificial Intelligence with TensorFlow. As the author of more programming books than he can count, he's excited to be working with and Coursera in producing video training. When not working with technology, he's a member of the Science Fiction Writers of America, having authored several science fiction novels, a produced screenplay and comic books, including the prequel to the movie 'Equilibrium' starring Christian Bale. Laurence is based in Washington State, where he drinks way too much coffee.



156 total reviews

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By Ben B on 17-Mar-19

This felt like a glorified tutorial for TensorFlow/Keras. I expected more in-depth treatment of the material. E.g. covering more ground (regularization wasn't mentioned at all), or going into more depth on the machine learning theory (why are we using this activation function, this loss, or this optimiser) or practical tips (e.g. discussions of network design) or the tools we are using (e.g. what exactly is TensorFlow, what is Keras, how do they relate to each other, how do they work under the hood).I also raised some issues and PRs on the github repo for the worksheets to correct problems in some of the worksheets, but these were not responded to by the time I had finished the course over a week later, despite the low volume of issues and PRs on that repo.I paid for the course upon getting to the first quiz so that I could have my answers graded, but I don't feel that I got my money's worth.

By Kristina P on 14-Mar-19

I was expecting a more elaborate content and graded programming exercises for those who pay for the course. Instead the major part of the content is based on the FREE tutorials available on TensorFlow website. Besides, the course is split to 4 weeks but the complexity of the content does not fit to the announced period. It can be easily completed within few days or less by any avearage CV researcher. It is populated with a bunch of very short videos with 'surface scratching' explanations. A targeted learner seems to be an undegrad. Also, some important concepts of TensorFlow were not explained (ex: what is tensor? etc.) Overall, I am disappointed and consider this a waste of money. eventhough, it can be useful as an audit for those who need some structure in self-education as it provides the sequence of tasks and some quizes as many other courses by Coursera.

By David T on 11-Mar-19

I like the CoLab Intro, and basics of Keras. But I think the 1st course are a bit too basic for someone who took the 5 courses Deep Learning Specialization. And it is too fast for someone who had not taken the DL courses. I would like the instructors to go over these topics in future courses: 1) TensorBoard and how to debug a faulty model2) TF 2.0 features (Eager execution, etc) 3) hands on example on how to fix the model if validation accuracy is much worse than training accuracy 4) LSTM models 5) how to productionize the model for real life use, like TF edge or TF.js

By Charles on 28-Apr-19

Far too basic - almost nothing about Tensorflow - graphs, tensors, estimators,, etc. The course is a bunch of pre-built examples using the Keras APIs to hit run on in Google collab. This is a very gentle introduction to Keras APIs, with no discussion of what's actually happening with Tensorflow.

By Mark B on 9-Mar-19

Often coursera courses are a bit easy / superficial. This course is a bit too much so. There's just not enough meat-on-the-bone for my liking. The instructor came across very well, the material is polished and professional, there's just not enough material for me to think of this as being a course. It only takes about an hour to do each weeks' material; the programming examples provide almost no challenge. As a first course on the topic this might be okay, but if you've done anything in this space before then it will be too easy. The course also uses the highest-level TensorFlow APIs; in a sense I wonder if this is really about TensorFlow when that same API is usable with other frameworks. I hope the rest of the specialisation has more detail.

By Raul D M on 14-Apr-19

Even if this course it is an introduction to TensoFlow, it is too easy. Good resources and good notebooks, the lectures are not bad and well explained, but the examination part is too soft.

By Olivier D on 2-Aug-19

This course barely touches what Tensorflow is and how it works, it is just a very basic introduction to Keras, and most of the time is spent explaining machine learning concepts rather than Tensorflow ones.

By Irina G on 2-Aug-19

I've finished the whole specialization in one week with 100% on all quizzes. I returned to its first course to rate it one star. I would give it 4 stars if the whole specialization was put in one free course "Shallow intro to TensorFlow with non-working and uninspiring examples". The intros with A.Ng are promising, big words and ideas, but the videos and examples are simplistic and don't deliver. There is no much work to do on this specialization, and I developed skepticism and mistrust toward the instructor. He doesn't come across as an experienced ML/TF practitioner, and some of his discussions are intentionally vague. It's incomparable in depth and content to Deep Learning specialization from the same It also dilutes the value of Coursera's Specialization. Please redo.

By Fengjun W on 18-Aug-19

Finally, wasted my weekend and 40 euros to finish this specialization. I really dont know the target audience of this specialization. If you have no background of deep learning, going through some code snippets without any explanation wont help you at all. you can't know anything behind it. If you already have some knowledge, you will find nothing new and more in this course. 1) The materials are so shallow and without any depth, just reading the slides and codes with errors. Only some high-level Keras APIs are covered. The official Tensorflow tutorial is much better. 2) The test questions are of no value at all, it cant test any your understanding whether about deep learning or the tool Tensorflow. The assignments are poorly designed, the answers contain errors. 3) I strongly doubt the instructor, I think he does not have much ML experience. Please don't waste your money and time on this specialization. If you want to learn deep learning, go to cs230; cs231n for computer vision; cs224n and cs224u for NLP; cs20 for Tensorflow.

By Oleg P on 8-Apr-19

Really disappointed. Please, give me back my money! This is not a course of Tensorflow but one page manual from Keras tutorial website. I hoped to learn the Tensorflow but have seen only some very simple examples with API wrapper for simple tasks and passed the course in a day. There was almost nothing from the Title of the course. The course should be free. There is nothing for $49 in it (except really cool teachers)

By Ehsan F on 28-May-19

Too basic. I took it to learn about tensorflow not deeplearning and it's like just a bit of each which is useless at the end. It's just the 'Hello world' example in TF.

By Ekwoge E B on 12-May-19

I had a great time going through this course. I had a lot of challenges but which made me love the course even more. While I'm excited to start the next course, would still like to go through certain areas of this course to get a better grasp on some areas. I'm grateful to Cousera for such a learning opportunity!