このコースについて

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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4の4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13時間で修了
英語
字幕:英語

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
共有できる証明書
修了時に証明書を取得
100%オンライン
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4の4コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
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13時間で修了
英語
字幕:英語

講師

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deeplearning.ai ロゴ

deeplearning.ai

シラバス - 本コースの学習内容

コンテンツの評価Thumbs Up97%(3,750 件の評価)Info
1

1

3時間で修了

Sequences and Prediction

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
2

2

3時間で修了

Deep Neural Networks for 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

3

3時間で修了

Recurrent Neural Networks for 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
4

4

3時間で修了

Real-world time series data

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

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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....
TensorFlow in Practice

よくある質問

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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