6 июня 2020 г.
I really enjoyed this course, especially because it combines all different components (DNN, CONV-NET, and RNN) together in one application. I look forward to taking more courses from deeplearning.ai.
3 авг. 2019 г.
It was an amazing experience to learn from such great experts in the field and get a complete understanding of all the concepts involved and also get thorough understanding of the programming skills.
автор: Edmund L C•
6 дек. 2019 г.
Excellent course that takes an amount of time right at what is specified in the program description. All learning is productive - you won't be spending hours teaching yourself how to program and debugging code, but will rather spend all time evaluating code to further your understanding of the concepts.
автор: Karl J•
29 дек. 2019 г.
A great course introducing syntax and application of TensorFlow to time series data. Does not go very deep, but pretty clearly is designed to show you how to apply the TensorFlow library to common situations rather than teach about time series and forecasting, which is a huge subject in and of itself!
автор: Rahul R•
9 окт. 2019 г.
Wonderful course........these courses tough me that there is always room for improvement. Just we need to try with small steps in the right direction. DL is not just achieved using algorithms but need patience and trial and error too. Thanks to Laurence Moroney and Andrew Ng for this wonderful course.
автор: Reza M•
28 авг. 2021 г.
This is a very good specialization. It helps you learn your way around TensorFlow and Keras and their knowledge base. You can literally build models in shortest formats like 5-10 cells after this. The usage of callbacks is covered as well which helps a lot in saving time and tuning model parameters.
автор: Niklas T•
8 дек. 2020 г.
Great Course, thank you Laurence and Andrew, as always I have enjoyed it very much! I think it was very helpful that in the first two weeks you explained everything step by step how to work with time series before moving on to how to make them work with NNs. Thank you, see you in the next course.
автор: Lijun L•
16 апр. 2020 г.
Wonderful class and it makes this complex task so simple. I really appreciate the hard work and effort from Laurence and Andrew to make this available to me. As what Laurence said, playing around those models and notebook will make a real difference on my machine learning skills. Thank you again!
автор: M B•
20 окт. 2019 г.
I absolutely love the deeplearning.ai courses. I previously took Andrew's course that went more into the theory, and this course was a fantastic compliment to it that focused more on putting deep learning concepts into practice via tensorflow. I look forward to any future courses they put out! :D
автор: YUJI H•
26 авг. 2020 г.
This is what I have wanted to study! When saying "Time Series Data" in the field of Deep Learning, they often only deal with text data and it means NLP. But in this course, we can study how to deal with real Time Series Data like Stock Price. Thanks for giving us the great examples of analysis!
автор: Gautam K•
21 июля 2020 г.
This course has been very great for learning sequences, time series and prediction code implementation in TensorFlow. This course is very helpful for beginners like me who are a newbie in TensorFlow.
Overall whole specialization has been really great and a small step towards learning DNN and ML.
автор: Daniel M•
17 нояб. 2019 г.
It was very nice to learn more about TensorFlow! Nice practice about real-world stuff. There's too much to learn, but I hope you get more courses in much different topics to connect all and get a better understanding of Artificial Intelligence possibilities! Thanks for teaching me this much!
автор: AKSHAY K C•
8 апр. 2020 г.
An absolute cracker of the course for Time Series and Predictions from Laurence Mooney and deeplearning.ai in a structured way building up the concepts fro the basics to real-world problems. Enjoyed every moment I did the course. Kudos to the entire team for delivering such good content.
автор: Ed M•
23 сент. 2019 г.
This is easily the best material I've seen on time series analytics using DL. Lawrence Moroney does an unbelievable job of demonstrating how to create a practical time series model using different architectures from start to finish in a completely understandable way. Thank you so much!
автор: Philippe B•
26 янв. 2020 г.
Je modélise des séries temporelles depuis des années. Une des motivations de ce cours était d'apprendre à utiliser les modèles de Deep Learning sur ce sujet. Grâce aux cours précédents et à celui-ci, je vais pouvoir concrètement utiliser ces modèles à la prévision de séries temporelles.
автор: Ryan B•
30 июня 2020 г.
Laurence did a great job in this course. The information was compressed just enough to where I could move swiftly but also still gain deep insight & intuition into the code so I can apply the tools to other projects outside of this course. Can't wait to start the next specialization!
автор: Martín C•
13 июня 2020 г.
Excelente curso, Laurence va explicando paso a paso, en forma detallada, como ir mejorando la DNN para obtener mejores resultados. Recomendado. ¡Lo disfruté!
Excellent course, Laurence explains step by step, in detail, how to improve the DNN for better results. Recommended. Enjoy it!
автор: Arpit K•
26 мар. 2020 г.
Amazing work by both Andrew NG and Laurence Moroney. I look forward to your next courses. Without these courses, it was very difficult for me to learn Artificial intelligence and because of these courses, I found my interest in AI. Thanks a lot, Andrew Ng for making these courses.
автор: Kazimierz T A H•
27 апр. 2020 г.
Thank you for a great set of courses! I really enjoed working with real datasets and being able to find out for myself how they worked. The content was at the right level for my Python programming ability and the Google Colab and Jupyter notebooks provided an easy place to learn.
автор: Suresh K M•
4 апр. 2020 г.
Thank you so much for providing such a great series of courses! It makes more sense as i've started from Machine Learning, Deep Learning Specialization and this TensorFlow in Practice Specialization. I'm happy that i've taken this course. I would expect to see more of the course.
автор: Wilder R•
11 сент. 2019 г.
I really enjoyed this one. The content on time series was good and I love TF2: it makes life so easy! I have done all the other courses from Andrew and at the beginning thought that this was was not going to help much. I'm really glad that Andrew and Laurence proved me wrong. :)
автор: Gourav S•
10 нояб. 2020 г.
Fantastic hands on introduction to using tensorflow and resoning with it using various approaches. An amazing starting point. Should be used along with the deep learning specialization course though in case you are interested in learning the fundamentals / maths a bit better.
автор: YOGESH H•
11 июля 2020 г.
Mr Laurence and Prof. Andrew Ng are one of the best mentors in the world with such an excellent,well framed, easy to grasp content that enables a beginner to grasp concepts and practices of such great frameworks of Deep Learning easily and provokes to learn more and more...
автор: Syed A A•
25 авг. 2020 г.
Really impressed by the work of the team. It is designed specially for the beginner to advance their career and be expert the emerging AI field. With the help of high quality videos and project based assignment one become expert hoe to deal and tackle real world problems.
автор: Surya K•
5 апр. 2020 г.
The "smaller" concepts in the videos were really the good stuff. Such as why MAE or Huber loss is better in some cases than MSE. This course was a little too "easy" since I had experience with PyTorch framework. I would recommend this course to early intermediate people.
автор: Rishi G V•
1 сент. 2019 г.
It is really an amazing course, Which gives me an core understanding of an Sequence, Time Series and Predictions concepts. Thanks for these beautiful course and especially my heartfelt thanks to our beloved lecturer Laurence Moroney and Andrew ng for these great platform
автор: Rana A•
12 апр. 2020 г.
I deal with time series quite frequently in my job and these techniques would be an interesting addition to my toolkit to get more meaningful inferences from that data. It is amazing how easy Laurence makes application of all these techniques and concepts in Tensorflow.