I do hope that the deeplearning.ai team could spend more time polishing the materials instead of just throwing the Tensorflow docs/sample codes and going through them superficially. Please also change the instructor as I really doubt his professionalism/experiences in ML practices despite his titles. Please, please don't ruin your brand, deeplearning.ai. I wish to see more in-depth courses like the ones taught by Andrew.

Great for learning the basics! Love the instructors. They have a great attitude, and their commitment just inspires us to try to give something back to the community as well.

The exercises were a bit not well-thought of. The data manipulations seemed too specific. Besides, reading the Numpy/Keras documentation is not always worthwhile for beginners. So that was a bit confusing. But if you are good at Python, that won't be a problem.

Keep up the good work, the deeplearning.ai team!

I enjoyed the last course of the practice in tensorflow. There is a lot of note books to work with, the teaching was good and good referencing. Simple to understand, even though we might require more notes and also materials to work on the local jupyter notebook. Some simple code could be a night mare as you are using windows machine, linux, anaconda. As the courses progressed, there are more and more references to work with. Looking forward to the next set of courses.

The course was wonderful. I can say time invested in this course help for my future AI journey.

As working in Automotive Industry as an Embedded Software engineer, I feel that I can use tesnsorflow library in so many application such as Machine Vision system for Factory Automation. I hope that I will try to develop an out the box solution using these learning. Throughout the course, I enjoyed learning. Thank you, Laurence, for the extra ordinary course.

Nice experience taking this course. Precise and to the point introduction of topics and a really nice way to start programming the models without going much into theory and a comprehensive and nice way to learn tensorflow framework. Mr. Laurence Moroney Sir has been excellent in all the courses and the conversations with Andrew sir are chilling as well as motivating. So its been a very good experience to take this specialization and learn tensorflow.

Guys you are the best, i commented to Laurence to about six months ago that i finded my vocation with your course, and with the firts course of this specialization i didn't understand anything and i did the Deep Learning Specialization and i am really fascinated with AI and deep learning. By the way I am a mathematician and thank to you i am a AI research with TensorFlow as a tool for coding and building DL and ML models.

Really Thank you

Very detailed step by step tutorials of using Tensorflow with lots of effort to make things as easy to understand as possible. Especially, examples of generation a time-series pattern simulations looks very thoughtful and helpful for the course topic. A little lack of theory comparing to other courses by deeplearning.ai. Quizzes are quite undeveloped. But that is understandable, because the main goal of the course to introduce Tensoflow.

Really enjoyed the course and it definitely helped a lot with my own projects. I guess the only thing I felt should be different were some of the quizzes. It seemed to me that there was too much attention given to questions regarding little nuances of the code, while I believe they would have been more interesting and significant if they focused more on theoretical concepts of forecasting and modeling. Overall great course, nonetheless!

Before enrolled in this course, I've finished deep learning specilization taught by Andrew. This course really help me put everything together. I really hope that Laurence and Andrew keep releasing the course like this further.

Special thanks to Laurence himself, I really enjoy the way he taught. the way he progressively show how every some line of code done something and the way he wrap up in each weeks :D

The overall course was good,. The topics were demonstrated nicely. However, the absence of programming assignment and assessments really keeps a hole within me questioning have I actually mastered it all. Would have been more fulfilling if there were some programming assignments, through there were chances for self-evaluation through given google colab assignments in the end of every week.

I needed wonderful course and wonderful code to make me understand the way to solve the 'Time Series' problem. My English skill is awful, but the professor explained so, so well that I could understand pretty well. I knew the concepts of the models before I take this course, but I didn't have any opportunity to see codes realized! Thank you very much for offering me such a nice lecture :)

Complicated ML-tasks as Sequence and Time-Series predictions are presented in a nice and easy-to-understand way (at least for me). Some of the techniques explained like image augmentation by ImageDataGenerator and creating synthetically datasets (especially time-series data) were new to me. So thank you for that nice course series and hope to see some more in the future.

I didn't know anything about TensorFlow, but i had been study from the Andrew Ng courses, that are more focused on the theory. This course is the perfect complement, with the applications.

The only thing is that i find a little short the course, but anyway very good. Thanks Laurence and I expect to have enough time to see your another specializations!

This specialization was the ideal evolution in my DNN training after having taken Andrew Ng's classic ML course, followed by the deeplearning.ai DNN specialization. The instructor is excellent, as are the lecture notes, training materials, coding platform and examples! I am moving on to Advanced ML w/ TensorFlow on Google Cloud

This specialization was exquisite from beginning to end. Without going deeper into the mathematics of the machine learning and deep learning algorithm we learned practical uses of such algorithms using TensorFlow. All the quizzes and homework taught us a variety of techniques. I am very satisfied with this course.

I like all of the 4 courses in the entire series. Dr Moroney offers you the codes and you can play around by yourselves to better understand the concepts and the algorithms. My suggestion is: You can watch the videos and pass all the tests first and download the codes, and later you can study the codes in details.

This course is different from the other 3 courses of this specialization as it teaches a new concept i.e Time series. This thing has not been taught in the deep learning specialization. But everything that has been taught in this course is well explained. I have my gratitude to Laurence sir 's way of teaching.

At first, I thought this was tragically oversimplified. Then I realised that the real benefit of this course is the practical walkthroughs that it in the large consists of. Other courses can give you the theoretical foundations of Machine Learning, but this excels as a treasure trove of practical guidance.

Really like the focus on practical application and demonstrating the latest capability of TensorFlow. As mentioned in the course, it is a great compliment to Andrew Ng's Deep Learning Specialization.

Very good Tensorflow ML tutorial. The explanation on data.DataSet needs to be more detailed.

Unfortunately this course does not do a great job in teaching in my opinion. The course states that it is around 25 hours, however the "teaching" portion of it totals to only about 2 hours of short videos, that don't do a great job of really explaining anything. The larger portion of the time is taken up by the labs, which are basically just sheets of unexplained code that you click play on to see what they do. At the end of each section, you have to take a quiz and a test. The quiz generally contains questions that are designed to just trick you into the wrong answer, with multiple choice options that all look similar. The tests are ok, however if you are unable to work out the answers there is no real help provided, apart from the ability to post on a forum for the course. In the forum you are unable to post any actual code, which means that the threads are just a mess of people trying to explain what they have tried without actually posting their code, and others trying to help them in the same way, which makes the forums practically useless to get help from. In the final test, you have to create a modal that needs to get MSE and MAE scores that are under a certain number to pass. These numbers are seemingly completely arbitrary, and since there is no available recourses to help yourself, and the forums provide little insight, the final test to attain the qualification just becomes based on random trial and error.

Thank you very much Mister Moronay and also your Team, You were able to clearly explain and show the different types of series and how to predict such using from simple to complex approaches. The labors are very sophisticated, thanks for your work to make these notebooks available. I have learned a lot especially the lambdas an the RateChangeScheduler were real cool information. I will keep learning leveraging your course Advanced Techniques Specialization. My summary is that it is pretty simple to create a model. The problems are to preprocess the data, because you have to learn a lot about the csv, numpy and so on Python APIs, and of course the tweaking of the different hyper parameters. Thanksfully the complexisity of them are "slightly" reduced within the notebooks So, see you next time PS.: The same opinion applies to the first 3 lectures of this specialization

Engaging and indepth . Watching only videos does not help but spending time on the lab and additional effort from your side will sky-rocket your progress . The instructor has somehow managed to condence such huge lessons in 2-3 minutes videos is beyond my brain to process . But that saves a lot of time and it does compromise with the content and quality of the course as well . So it's a win-win situation . I find that the codes in the lab are a bit hard to understand as I'm not too experienced in python and the notebooks will be a good reference point for my future projects . prerequisites - * Deep Learning Specilization * Proficiencyin python and numpy I wanna thanks the course instructor Lawrence and also Andrew for making this course . This has been a great help for me in my way to become a ml engineer . So thank you .

Personally I loved this course, I had a previous knowledge of this topic, because it's one of my favorites topics (very related to IoT analysis data). And here I've learned various top technics suchs lambda layers, or that we have to split in training, validation and testing periods the data. This is something that you don't see in many books or manual about time series with tensorflow. And finally I've learned very useful libraries that I even didn't know that exists like tf.keras.dataset, that makes so easy to give format to the data, before you had to write more code. So with this information I can write more effective and efficient code! Thanks Laurence and Andrew from Perú!

The "Sequences, Time Series and Prediction" course by deeplearning.ai is a comprehensive guide to handling sequential data using TensorFlow. It offers an effective balance between core theoretical concepts and their practical application in machine learning. The assessments are well-designed, providing hands-on experience with TensorFlow for tasks like model creation, dynamic learning rate adjustment, and real-world time series data handling. The course could benefit from more detailed code explanations and context on choosing optimizers. Overall, it's an excellent resource for understanding and implementing time series prediction models.