Laurence Moroney
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 Specialization will teach you best practices for using TensorFlow, a popular open–source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real–world data! 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 deeplearning.ai 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. deeplearning.ai is Andrew Ng’s new venture which amongst others, strives for providing comprehensive AI education beyond borders.
Instructor Details
Courses : 8
Specification: Sequences, Time Series and Prediction
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69 reviews for Sequences, Time Series and Prediction
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 8 hours |
| Year | 2019 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Alice M –
expand on why you choose certain code. add more references for learning python better
Tyler L –
Great start for anyone with an interest in machine learning!
Ulugbek D –
I love this course! Especially, how the instructor introduces ways of varying certain hyperparameters to achieve optimal results.
Muthu R P E –
Great course with in depth knowledge of LSTM ! but not how LSTM is used on all practical applications.
Robert G –
I would like to see forex and stocks.
AasaiAlangaram –
Working With Sunset Kaggle Dataset was interesting.Waiting for upcoming courses in deep learning.
Giridharan A –
A vast portion covered with few videos.
Amir H –
Thank you for this very interesting and informative course. I really enjoyed the simplicity in explanation and the hands on implementations. One thing that I think will improve this course further is to add more intuition and explanation of using particular structures like CNN followed by LSTM.
Mukkul N K –
Really an awesome course. Full of knowledge.
Samarjeet S –
Good course
Charlie C –
No concrete knowledge, no solid explanation. Just some demo.
vikas c –
Good course
Mani S –
Nice and easy paced.
mehryar m –
I’m so glad to take this course and build my knowledge regarding time series data and modern approaches to create prognostic models. Thanks to Andrew Ng and L. Moroney to provide this course.
Karl J –
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!
Aroua G –
Lots of good techniques and helper functions to work with time series. I wish there was more variety in the problems encountered (rather than prediction some time series classification for instance) but that doesn’t affect the good quality of learning provided.
Ahmet K –
Easy to learn and follow, thanks guys. Thank you coursera…
Nitin K M –
The courses are well oriented and give a good introduction to TensorFlow.
Shuhei O –
fun, great course, great instructor
Aleksey V –
Would ask more difficult tasks to solve, the level is just entry
Alvaro M A N –
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 Peru!
Amardeep S –
Homework assignments should be required.
Laura U –
Love it. Thanks Laurence for making the course accessible.
Efstathios C –
Thank you!
Lydia N –
Wonderful Course splendidly and thoughtfully compiled sets of hands on exercises and information explaining how to use TensorFlow.
Jussi H –
I wanted to like this specialization, but I just cannot. My expectation was that this specialization would complement Andrew Ng’s excellent Deep Learning specialization, but it does not. Whereas the DL specialization taught you best practices and a systematic approach to improving models, this specialization throws all of that out the window. The architectures are downright silly in some of the examples. If you want to learn TensorFlow, you would spend your time more wisely by working through the official TF tutorials, which are pretty good.
Muthiah A –
I enjoyed the thoughtful exercises and measured experienced guidance of Laurence (who has been doing this for years now in big stage). It’s a bite sized introduction to Tensorflow aspects for busy professionals and while you can “game” the quizzes and earn completion, really the onus is on learner to spend time on reading materials and videos and great colab exercises. Google Colab notebooks are single outstanding reason this whole specialization is compelling to me. Thanks everyone @ Coursera
Sai K K K –
Concepts and Importance of Fine tuning the parameters well explained!!
Gamage O I –
This is an good introductory course. It is better if you can grade computer assignments also.
sheetal –
Worth it.
rajesh t –
need to be more advanced, with realistic data and problems. Do not use textbook data.
Jiawei X –
This course is great for introduction. BUT it is still lacking very important background information of the Tensorflow Dataset and how to master it. It makes sense not to go into too deep on the NN model and their theories but when it comes to practical usage of any machine learning packages, data pipelines play very significant role (count towards 60% 70% of the codes). In the course we briefly talk about Dataset and use only a few APIs without explaining why and the logic behind them. And tutorials from tensorflow’s officials still lacking useful guidelines when dealing with dataset of multiple dimensions.
Gabor H –
Very thanks the lot of samples and explanations.
afshin m –
This course is much better organized than the NLP (3rd) course.
Vahid N –
It is very easy to follow this course. I wish some function/object options and arguments (such as why we use Y^hat (hat is usually reserved for estimated values) and not Y in LSTMs) were explained in more detail for curious readers.
Barclay B –
Excellent course!
jaime c –
Excellent, an interesting and practical point of view
Xueming L –
Thanks for the great course, it’s very practical knowledge on how to use tensorflow to build up models.
Mohammad Z –
Really Nice
Arkady T –
Good practice in TensorFlow 2.0
Akshay s –
This is just univariate time series . You should also teach multivariate time series.
Andres R –
Ok, this course was amazing, cause i pass a big large course in Udemy about Data Science for get a right way to complete my master degree tesis, and it was not enough for my, this course will help me to use my own data set that have been streamed for some sensors to analysed and predict them, before this course i don’t know that CNN and LSTM is a right way to work with time series but, nowadays i know that is a good way, congrats Laurence and Andrew.
Philippe B –
Je modelise des series temporelles depuis des annees. Une des motivations de ce cours etait d’apprendre a utiliser les modeles de Deep Learning sur ce sujet. Grace aux cours precedents et a celui ci, je vais pouvoir concretement utiliser ces modeles a la prevision de series temporelles.
Jonathan P –
Extremely understandable! Brilliant course!
Victor C –
after andrew’s course, this course is really helpful for learning a new tool
Pablo J B –
I would have like to do testing exercises.
Alex F –
A challenging journey to learn Sequences and Time Series to deal with the real world, which is of much fun in the course. Let’s explore together.
David P –
A great course, wrapping up the specialization. The entire specialization has been very informative and inspirational. Thank you Laurence and thank you Andrew. Like many others, would love to see what you produce next.
peropop –
Nice course. Despite it’s a practical one, you should consider to get just some deeper in the theory embedding the models you presented, to make the audience understand better what’s going on.
Khin R P P –
Thank u for this course. But i still need learning about more time series. Hoping new lectures video coming soon.
Maxime C –
Great course
Ramji B –
Really a good course to start off with time series modeling, Thank you Lawrence and Andrew : )
Chirag S –
Amazing course!
Armand d P –
Super clear and concise course. I think it is great fundamental practicalnstuff.
Raul D M –
It is the most interesting course of this specialization.
MUHAMMAD M M –
so amazing!
Govind M –
It was amazing. Learnt lots of techniques and i am looking forward to learn more from this team.
Asad M –
It’s a relatively shallow course. They don’t really dive down to the details or even don’t cover whole a lot when it comes to examples, exercises or assignments. So, This is very much for the beginners.
Tomasz D –
Course is very quick and does not cover the topics in sufficient depth explanations and discussion are all very brief.
MOHAMMAD A U –
Excellent course. Till now i could not imagine how to use machine learning in time dependent data. This course will help me a lot in this regard I would like to thank Laurence Sir and a Special thanks to Andrew Sir
Abhiram V –
The content and visualization helps to understand the problem so well
Christoph H –
T H A N K Y OU
Kirill S –
A lot of repetition of the same methods, no clear indication on how exactly to tune the chosen NNs (for instance, how to select their order, how to tune optimzers’ parameters, etc) + extremely simple quizes. In general, it looks like this whole specialisation was designed just to earn some money on a existing deeplearning.ai brand. Huge disappointment.
Nguyen X D –
Really awesome !!!
Arpit k –
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.
Gerard S S –
First of all congratulations on the specialization. I felt that I have improved a lot my previous knowledge of Machine Learning and programming with Python and TS. One improving note:I felt that this course could go to third place in the specialization. You go deeper in CNN and LSTM which I missed in the previous one 🙂 Also, it would be great 2 examples of real world scenarios
Siddhartha P –
Few hands on programming assignments could be better for experience as was the case with starting two courses. Overall good course and the structure was well laid. Thanks for building it up
james b –
No graded exercises at the end of the practicals. Some of the quiz questions seems to be based more around general python and in 1 situation around the presenters only thoughts. Some information about estimating optimal learning rates was incorrect and misleading
Magdalena S –
Too easy.