In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader.
提供方


課程信息
At the rate of 5 hours a week, it typically takes 4 weeks to complete this course.
您將獲得的技能
- Deep Learning
- Inductive Transfer
- Machine Learning
- Multi-Task Learning
- Decision-Making
At the rate of 5 hours a week, it typically takes 4 weeks to complete this course.
提供方

deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
授課大綱 - 您將從這門課程中學到什麼
ML Strategy
Streamline and optimize your ML production workflow by implementing strategic guidelines for goal-setting and applying human-level performance to help define key priorities.
ML Strategy
Develop time-saving error analysis procedures to evaluate the most worthwhile options to pursue and gain intuition for how to split your data and when to use multi-task, transfer, and end-to-end deep learning.
審閱
- 5 stars82.81%
- 4 stars13.77%
- 3 stars2.80%
- 2 stars0.46%
- 1 star0.12%
來自STRUCTURING MACHINE LEARNING PROJECTS的熱門評論
Loved the course, and the simulation was great. Doing an actual transfer learning programming exercise in TensorFlow could be an awesome addition. Best & thanks again for an awesome course!\n\nEric
I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
關於 深度学习 專項課程
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.

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