Welcome to the Art and Science of machine learning. This course is delivered in 6 modules. The course covers the essential skills of ML intuition, good judgment and experimentation needed to finely tune and optimize ML models for the best performance. You will learn how to generalize your model using Regularization techniques and about the effects of hyperparameters such as batch size and learning rate on model performance. We’ll cover some of the most common model optimization algorithms and show you how to specify an optimization method in your TensorFlow code.
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来自ART AND SCIENCE OF MACHINE LEARNING的热门评论
thanks for the great work. There is so much to learn and I appreciate the effort you made to break things down and providing lab while making the hard decisions on what to commit.
This course is so really good to learn about the general knowledge and skill of Data Science like optimization batch or regularization and so on with Google Cloud Platform.
This final course is also very good. Embedding is my favorite part and Lak is my favorite instructor. Thanks Googlers! Looking forward to the next five courses.
A lot of core neural network topics were presented in a productive way and I particularly liked the LAB showing how to write custom estimators.
该课程是 Coursera 上提供的为数不多的课程之一，目前只对已购买课程或已获得助学金的学生开放。
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Last Updated: September 1, 2015