Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of data science problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way that supports experimentation.
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來自LAUNCHING INTO MACHINE LEARNING的熱門評論
Amazing course. For a beginner like me, it was a shot in the arm. Excellent presentation very lively and engaging. Hope to see the instructor soon in a another course. Thanks so much. I learned a lot.
This is an awesome module. It will open up so much inside story of ML process which is core of the topic with such a simplicity. It greatly increases my interest into this topic and this course :)
Good course, covering all the basics about machine learning and most importantly, everything that surrounds an ml project and you need to take into account to make your ml project successful.
My favourite course in the specialisation. I think it's a great idea to use historic time-frame to explain the advances in ML and why there is so much hype around deep learning.
關於 Machine Learning with TensorFlow on Google Cloud Platform 專項課程
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。