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
You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.
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
- Forecasting
- Machine Learning
- Tensorflow
- Time Series
- prediction
You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.
シラバス - 本コースの学習内容
Sequences and Prediction
Deep Neural Networks for Time Series
Recurrent Neural Networks for Time Series
Real-world time series data
レビュー
- 5 stars76.82%
- 4 stars16.59%
- 3 stars4.06%
- 2 stars1.23%
- 1 star1.27%
SEQUENCES, TIME SERIES AND PREDICTION からの人気レビュー
An exceptional course design to enable practicing with ready code and teaching what actually runs in LSTM / DNN models. With this momentum, anyone will continue on another course.
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.
The course is easy to follow and focuses on how to implement theoretical concepts using tensor flow. The way Lawrence approaches the sessions makes it really interesting and fun to learn!
I really enjoyed this course, especially because it combines all different components (DNN, CONV-NET, and RNN) together in one application. I look forward to taking more courses from deeplearning.ai.
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