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.
Sequences, Time Series and Prediction
Sequences, Time Series and Prediction
This course is part of DeepLearning.AI TensorFlow Developer Professional Certificate
Instructor: Laurence Moroney
143,166 already enrolled
Gain insight into a topic and learn the fundamentals.
4.7
(5,085 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 21 hours
Learn at your own pace
97%
Most learners liked this course
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
Skills you'll gain
- Category: prediction
- Category: Tensorflow
- Category: Forecasting
- Category: Time Series
- Category: Machine Learning
Details to know
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Assessments
4 assignments
Taught in English
Build your Machine Learning expertise
This course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate
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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 videos7 readings1 assignment1 programming assignment2 ungraded labs
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 videos2 readings1 assignment1 programming assignment3 ungraded labs
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 videos4 readings1 assignment1 programming assignment2 ungraded labs
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 videos9 readings1 assignment1 programming assignment2 ungraded labs
Instructor
Instructor ratings
4.7 (771 ratings)Laurence Moroney
DeepLearning.AI
19 Courses531,442 learners
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DeepLearning.AI
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4.7
5,085 reviews
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PA
5
Reviewed on Apr 24, 2021
The course is overall amazing, the notebooks and videos given go hand in hand to build student's understanding. However, the video sound is too soft, using high volume is recommended
JH
5
Reviewed on Mar 21, 2020
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.
AK
5
Reviewed on Jun 4, 2020
Laurence Moroney is the best. Before taking up the course, i didnt know anything about the AI or ML or Tensorflow. The concepts were explained in such a manner that anyone can learn Tensorflow.
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