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This Specialization is intended for machine learning researchers and practitioners who are seeking to develop practical skills in the popular deep learning framework TensorFlow. The first course of this Specialization will guide you through the fundamental concepts required to successfully build, train, evaluate and make predictions from deep learning models, validating your models and including regularisation, implementing callbacks, and saving and loading models. The second course will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. You will use lower level APIs in TensorFlow to develop complex model architectures, fully customised layers, and a flexible data workflow. You will also expand your knowledge of the TensorFlow APIs to include sequence models. The final course specialises in the increasingly important probabilistic approach to deep learning. You will learn how to develop probabilistic models with TensorFlow, making particular use of the TensorFlow Probability library, which is designed to make it easy to combine probabilistic models with deep learning. As such, this course can also be viewed as an introduction to the TensorFlow Probability library. Prerequisite knowledge for this Specialization is python 3, general machine learning and deep learning concepts, and a solid foundation in probability and statistics (especially for course 3).
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
完成課程大約需要 4 個月
建議進度:7 小時/週
英語(English)
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
完成課程大約需要 4 個月
建議進度:7 小時/週
英語(English)

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此專項課程包含 3 門課程

課程1

課程 1

Getting started with TensorFlow 2

4.9
347 個評分
125 條評論
課程2

課程 2

Customising your models with TensorFlow 2

4.8
107 個評分
45 條評論
課程3

課程 3

Probabilistic Deep Learning with TensorFlow 2

4.7
46 個評分
17 條評論

提供方

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伦敦帝国学院

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