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Sequences, Time Series and Prediction

This course is a part of TensorFlow in Practice, a 4-course Specialization series from Coursera.

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.

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Rating 4.4 based on 194 ratings
Length 5 weeks
Effort 4 weeks of study, 4-5 hours/week
Starts Feb 17 (last week)
Cost $50
From deeplearning.ai via Coursera
Instructor Laurence Moroney
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Software Development Machine Learning

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What people are saying

According to other learners, here's what you need to know

time series in 36 reviews

Really a good course to start off with time series modeling, Thank you Lawrence and Andrew :-) Great course Amazing and awesome course by coursera ...Lawrence is an amazing tutor with lots of energy.

But i still need learning about more time series.

after andrew's course, this course is really helpful for learning a new tool 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.

This is just univariate time series .

You should also teach multivariate time series.

This is something that you don't see in many books or manual about time series with tensorflow.

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!

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.

I needed wonderful course and wonderful code to make me understand the way to solve the 'Time Series' problem.

Great to finally confidently apply ML to Time series !

I eager to learn Time Series Analysis.

I found it great for the following reasons:- Laurence Moroney (Instructor) was very professional and clear while delivering the knowledge- The introductions by Andrew NG were really nice- Easy to understand codes and understanding of thr underlying principles- Varied topics such as CNN, NLP & Time Series- Very insightful by providing expert opinions about different ways of model optimizationI really enjoyed the course and I thank the instructor for the same :) 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.

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deep learning in 20 reviews

Une des motivations de ce cours était d'apprendre à utiliser les modèles de Deep Learning sur ce sujet.

My expectation was that this specialization would complement Andrew Ng's excellent Deep Learning specialization, but it does not.

It gives a good foundation to learn more about deep learning and its numerous applications.

The best deep learning lecture ever!

Very nice collection of useful tools for machine learning and deep learning.

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.

The concepts from Deep Learning specialization by Prof. Andrew has explained well here for Keras.

Thanks for all this knowledge This is a great course but I will advise taking Andrew's "Deep Learning Specialization" before this.

As a graduate of the Deep Learning specialization, I expect this to be a way to apply that theory to large datasets and to novel architectures requiring some leverage of the lower level tensorflow APIs.

It was a brilliant course , I thoroughly enjoyed learning various aspects and techniques of Deep Learning techniques and in the process also learned a lot about TensorFlow .

I finished whole Deep Learning Specialization and I LOVED IT.

Good Good course it gives you quick start on practical aspects of Deep Learning techniques.

If you have no background of deep learning, going through some code snippets without any explanation wont help you at all.

2) The test questions are of no value at all, it cant test any your understanding whether about deep learning or the tool tensorflow.

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andrew ng in 8 reviews

Thanks to Andrew Ng and L. Moroney to provide this course.

I only wish there were auto-graded notebooks in addition to the quizzes like in some of the other courses by Andrew Ng.

Thanks for these beautiful course and especially my heartfelt thanks to our beloved lecturer Laurence Moroney and Andrew ng for these great platform good It will be better if there is also a multivariate time series example.

!Quite disappointed about this sequence after the awesome other 3 courses taught by Andrew Ng.

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work with in 5 reviews

a little bit to light I would like to have more info on window and batch sizes - seems to be pretty important values to work with, but they are not covered in depth.In general, greate course that shows how to prepare sequences, feed them in to NN.Loved it.

This course was my ultimate motivator and goal for taking the specialization as I am doing work with time series.

As the courses progressed, there are more and more references to work with.

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Coursera

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deeplearning.ai

Rating 4.4 based on 194 ratings
Length 5 weeks
Effort 4 weeks of study, 4-5 hours/week
Starts Feb 17 (last week)
Cost $50
From deeplearning.ai via Coursera
Instructor Laurence Moroney
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Software Development Machine Learning

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