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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이 강좌에 대하여
You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.
배울 내용
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
귀하가 습득할 기술
- 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.
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강의 계획표 - 이 강좌에서 배울 내용
Sequences and Prediction
Deep Neural Networks for Time Series
Recurrent Neural Networks for Time Series
Real-world time series data
검토
- 5 stars76.82%
- 4 stars16.58%
- 3 stars4.07%
- 2 stars1.23%
- 1 star1.27%
SEQUENCES, TIME SERIES AND PREDICTION의 최상위 리뷰
The course is fantastic. It was a bit short and with some hyperparameters tuning focus, it could have been great. Also, it seems that it is biased to show that LSTM is always superior to RNN networks.
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
taking this course was undoubtedly a better idea than endless scans over tensorflow documentation and other books. I am glad I got to do this course, wish I had taken this up earlier
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.
DeepLearning.AI TensorFlow 개발자 전문 인증서 정보

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