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.
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このコースについて
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学習内容
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
習得するスキル
ForecastingMachine LearningTensorflowTime Seriesprediction
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自分のスケジュールですぐに学習を始めてください。
次における2の2コース
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中級レベル
You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.
約8時間で修了
推奨：4 weeks of study, 4-5 hours/week
英語
字幕：英語
シラバス - 本コースの学習内容
3時間で修了
Sequences and Prediction
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!
3時間で修了
10件のビデオ （合計33分）, 3 readings, 3 quizzes
10件のビデオ
Time series examples4 分
Machine learning applied to time series1 分
Common patterns in time series5 分
Introduction to time series4 分
Train, validation and test sets3 分
Metrics for evaluating performance2 分
Moving average and differencing2 分
Trailing versus centered windows1 分
Forecasting4 分
3件の学習用教材
Introduction to time series notebook10 分
Forecasting notebook10 分
Week 1 Wrap up10 分
1の練習問題
Week 1 Quiz
3時間で修了
Deep Neural Networks for Time Series
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!
3時間で修了
10件のビデオ （合計27分）, 5 readings, 3 quizzes
10件のビデオ
Preparing features and labels4 分
Preparing features and labels3 分
Feeding windowed dataset into neural network2 分
Single layer neural network2 分
Machine learning on time windows37
Prediction2 分
More on single layer neural network2 分
Deep neural network training, tuning and prediction4 分
Deep neural network3 分
5件の学習用教材
Preparing features and labels notebook10 分
Sequence bias10 分
Single layer neural network notebook10 分
Deep neural network notebook10 分
Week 2 Wrap up10 分
1の練習問題
Week 2 Quiz
3時間で修了
Recurrent Neural Networks for Time Series
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...
3時間で修了
10件のビデオ （合計20分）, 5 readings, 3 quizzes
10件のビデオ
Conceptual overview2 分
Shape of the inputs to the RNN2 分
Outputting a sequence1 分
Lambda layers1 分
Adjusting the learning rate dynamically2 分
RNN1 分
LSTM1 分
Coding LSTMs2 分
More on LSTM1 分
5件の学習用教材
More info on Huber loss10 分
RNN notebook10 分
Link to the LSTM lesson10 分
LSTM notebook10 分
Week 3 Wrap up10 分
1の練習問題
Week 3 Quiz
3時間で修了
Real-world time series data
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.
3時間で修了
11件のビデオ （合計24分）, 5 readings, 3 quizzes
11件のビデオ
Convolutions58
Bi-directional LSTMs3 分
LSTM1 分
Real data - sunspots3 分
Train and tune the model3 分
Prediction1 分
Sunspots1 分
Combining our tools for analysis3 分
Congratulations!38
Specialization wrap up - A conversation with Andrew Ng2 分
5件の学習用教材
Convolutional neural networks course10 分
More on batch sizing10 分
LSTM notebook10 分
Sunspots notebook10 分
Wrap up10 分
1の練習問題
Week 4 Quiz
レビュー
4.6
SEQUENCES, TIME SERIES AND PREDICTION からの人気レビュー
ORによりAug 3, 2019
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.
JHにより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.
VVによりNov 25, 2019
Great course! The notebooks were a great help for understanding the material. I only wish there were auto-graded notebooks in addition to the quizzes like in some of the other courses by Andrew Ng.
MMによりDec 26, 2019
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.
SPによりMar 26, 2020
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
WGによりAug 15, 2019
Though I feel some aspects of this course did not delve deep enough into the explanations of some functions, the course helped me understand how to use models for time series problems.
MKによりAug 2, 2019
This was really a beautifully designed course. They didn't focused on teaching too much of thing at once but build up the base slowly and strongly for better understanding.
CSによりNov 30, 2019
Great introduction to TensorFlow. Very broad coverage of the tools available in TensorFlow for Machine learning. Everything you need to get started on your first project!
PSによりSep 13, 2019
An excellent course on Time Series and Sequences by Laurence Moroney. Explained how to use CNN, RNN and DNN together to bring the nest out of time series prediction.
DDによりMar 31, 2020
Short, concise, and practical. But maybe, it'd be better if some more practical examples are addressed that clearly shows the power of the (CNN-)LSTM model over DNN.
AVによりNov 25, 2019
Thank you Laurence sir and Andrew sir for putting together this course. It gives a good foundation to learn more about deep learning and its numerous applications.
GGによりAug 4, 2019
Fantastic course, starting from basic fundamentals of statistical forecasting to using Convolutional neural networks. I will use my learnings directly to my job.
deeplearning.aiについて
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
TensorFlow in Practice専門講座について
Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.
In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry!
AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects.
Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization.
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