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Learner Reviews & Feedback for Building Deep Learning Models with TensorFlow by IBM

4.4
stars
861 ratings

About the Course

Deep learning is revolutionizing many fields, including computer vision, natural language processing, and robotics. In addition, Keras, a high-level neural networks API written in Python, has become an essential part of TensorFlow, making deep learning accessible and straightforward. Mastering these techniques will open many opportunities in research and industry. You will learn to create custom layers and models in Keras and integrate Keras with TensorFlow 2.x for enhanced functionality. You will develop advanced convolutional neural networks (CNNs) using Keras. You will also build transformer models for sequential data and time series using TensorFlow with Keras. The course also covers the principles of unsupervised learning in Keras and TensorFlow for model optimization and custom training loops. Finally, you will develop and train deep Q-networks (DQNs) with Keras for reinforcement learning tasks (an overview of Generative Modeling and Reinforcement Learning is provided). You will be able to practice the concepts learned using hands-on labs in each lesson. A culminating final project in the last module will provide you an opportunity to apply your knowledge to build a Classification Model using transfer learning. This course is suitable for all aspiring AI engineers who want to learn TensorFlow and Keras. It requires a working knowledge of Python programming and basic mathematical concepts such as gradients and matrices, as well as fundamentals of Deep Learning using Keras....

Top reviews

ZR

Jul 2, 2020

Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!

DO

May 26, 2020

Not so often i wish a course would be longer and more in depth I really enjoyed using TF I'll look some other courses about it

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76 - 100 of 178 Reviews for Building Deep Learning Models with TensorFlow

By Luis C M R

Feb 23, 2022

Really clear!

By Branly L

Apr 27, 2020

Very Good..!!

By Aditya M P

Dec 8, 2020

Good Course

By Samira G

Jun 1, 2020

Love it....

By Gift S

Jul 24, 2024

it is best

By Victor M C

Jun 30, 2024

BUEN CURSO

By Sandipan C

Aug 29, 2021

Nice Info

By Nikhil K

Sep 25, 2024

dqqqddwd

By Amritpal K D

Oct 21, 2023

Awesome

By Takahide M

Jan 6, 2023

Awesome

By Krishna H

Apr 27, 2020

Good!!

By 01fe21bec413

Apr 24, 2024

Good

By Lim S

Mar 1, 2022

good

By Roger P

Aug 31, 2021

This is a good introduction to Tensorflow. Like all Coursera courses I've experienced to date, there were plusses and minuses.

The good side of each of these courses: * The courses cover the main concepts (building models, limitations, challenges, etc). They covered activation functions, Convolutions, width and depth of models, Gradient Descent and learning rate issues.

* The lessons don't oversimplify, but give you the tools you need to explore further on your own if you wish.

* Replies to my forum questions were actually surprisingly quickly answered. I was expecting the forums to be filled with months-old unanswered questions.

* Being able to replay videos was invaluable.

The less-good side:

* The exams are token, often multiple choice with unlimited retries. That is fine.

* The lessons are often replete with misspellings, grammar errors and ambiguous quiz questions.

* Sometimes, due to the stochastic nature of ML models, the errors/mispredictions differ between the Grading Rubrics and legitimately obtained results.

Would I do it again? My answer is this- I feel for six courses I have the equivalent of one junior-level semester survey course's worth of information and experience. However I was able to do it on my own time starting immediately, at my own pace, replaying the lectures at will and all for a tiny fraction of the cost and time of a college course. I do believe I have a starting point to pursue more advanced topics and for that I believe it was well worth it.

By Prent R

Dec 7, 2021

I felt the labs failed to illustrate the reasons why we were learning the concepts. They did not use examples that would have shown how the tools would have value with real projects. For example: Building Deep Learning Models with TensorFlow/ML0120EN-3.1-Reveiw-LSTM-basics only illustrated some very limited concepts. Instead of an example that had value, it was just variables and numbers. The same is true for labs_ML0120EN-3.2-Review-LSTM-LanguageModelling_with_results.ipynb. It did not actually model anything of relevance. It had a section on # Define the gradient clipping threshold, without explaining why that is important. This was true with most of the exercises. When I compare that with a course like Introduction to Deep Learning & Neural Networks with Keras the differences are vast. Keras is a simple interface and all the examples were clear and had real world applications for business. Not so with this course. A huge disappointment, and a terrible waste of time.

By Omri

Aug 13, 2020

This is a great course and a great instructor. I also loved his course on Machine Learning with Python. My major criticism, relevant also for the course on Keras in the AI Engineering program, is that the lectures and labs are not updated to the new versions of packages. The new versions of Tensorflow, Tensorflow2.0, were changed significantly relative to the version used here. Moreover, Keras in now TensorFlow's official high-level API, which means that the code learned in these courses cannot be used for new data without implementing the new syntax of these libraries. I hope IBM will update the learning material more frequently so these wonderful courses will keep being relevant.

By A A A

Jul 7, 2020

The instructor Saeed Aghabozorgi did an excellent job in explaining the concepts in a way everything can be understood easily. However, I still think 5 weeks is not enough for this course, given TensorFlow is more difficult to learn than PyTorch. The basics could be covered in more detail, including the tf.get_variable(), tf.gradient(), calculating gradients and other functions that were used. There could be a lecture for Linear Regression and Logistic Regression and these 2 could be moved to a separate week instead. Also, please upgrade the code to work on TensorFlow 2.1. The current code designed for TensorFlow 1.8 didn't work especially the part where datasets are to be loaded.

By bob n

Oct 15, 2020

Four stars because some of the labs (and none of the lectures) have not been brought up to the current version of TensorFlow. There are significant differences between 1.x and 2.x, especially in the paralell processing. I don't expect a course to send me on wild goose chases across the internet having to bring their examples up to current versions. I guess you get what you pay for, no surprise that Big Blue isn't current.

By Txomin V

May 11, 2023

A good introduction to AI networks in raw Tensorflow without heavy reliance on Keras, definitively matched my expectations!

The LSTM model and Restricted Boltzmann Machine explanations were quite hard to follow and I had to resort to other websites to learn more about the basics of these topics...

Otherwise, very interesting and I would definitively recommend it!!

By Michael S

Mar 26, 2020

Very interesting material, and easy to follow along. The notebooks are a great resource. I am glad to have been introduced to these concepts. However, I felt this course was too easy and it did not encourage the student to complete projects or any independent work. In any case, this course was worth taking.

By James R

Dec 22, 2019

I liked the course; however, there was no sound or transcripts for the last week of the course. This required me to research all the topics that I saw on the screen. Still a good learning experience but put more responsibility on me to learn the topics.

By Dimitrios D

Feb 8, 2024

Building Deep Learning Models with TensorFlow Has a lot of math explanation and good visuals, but lacks training cells for the labs and there are no questions during the videos. If you want to practice Tensorflow, you´ll have to do it on your own.

By Edward J

Oct 20, 2020

Interesting course but I wish there were more opportunities to add code myself or even a proper task. I was sad not to have videos from Romeo. However, I thought that the explanations of the different deep learning models were very clear.

By Alessandro F

Apr 5, 2021

Quite a basic course, you don't get to learn much of tensorflow. This is an introduction to some deep learning models, the content is clear and the course it is well-structured, but it does not go very much in depth.