DeepLearning.AI
Sequences, Time Series and Prediction
DeepLearning.AI

Sequences, Time Series and Prediction

Laurence Moroney

Instructor: Laurence Moroney

137,342 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.7

(5,020 reviews)

|

97%

Intermediate level

Recommended experience

22 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Solve time series and forecasting problems in TensorFlow

  • Prepare data for time series learning using best practices

  • Explore how RNNs and ConvNets can be used for predictions

  • Build a sunspot prediction model using real-world data

Details to know

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Assessments

4 quizzes

Taught in English

Course

Gain insight into a topic and learn the fundamentals

4.7

(5,020 reviews)

|

97%

Intermediate level

Recommended experience

22 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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This course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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  • Gain a foundational understanding of a subject or tool
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There are 4 modules in this course

Hi Learners and welcome to this course on sequences and prediction! In this course we'll take a look at some of the unique considerations involved when handling sequential time series data -- where values change over time, like the temperature on a particular day, or the number of visitors to your web site. We'll discuss various methodologies for predicting future values in these time series, building on what you've learned in previous courses!

What's included

10 videos8 readings1 quiz1 programming assignment

Having explored time series and some of the common attributes of time series such as trend and seasonality, and then having used statistical methods for projection, let's now begin to teach neural networks to recognize and predict on time series!

What's included

10 videos5 readings1 quiz1 programming assignment

Recurrent Neural networks and Long Short Term Memory networks are really useful to classify and predict on sequential data. This week we'll explore using them with time series...

What's included

8 videos6 readings1 quiz1 programming assignment

On top of DNNs and RNNs, let's also add convolutions, and then put it all together using a real-world data series -- one which measures sunspot activity over hundreds of years, and see if we can predict using it.

What's included

11 videos11 readings1 quiz1 programming assignment

Instructor

Instructor ratings
4.7 (754 ratings)
Laurence Moroney
DeepLearning.AI
16 Courses498,133 learners

Offered by

DeepLearning.AI

Recommended if you're interested in Machine Learning

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