This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with PyTorch, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more).
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
- 5 stars74.67%
- 4 stars20.66%
- 3 stars2.77%
- 2 stars0.63%
- 1 star1.24%
来自INTRODUCTION TO MACHINE LEARNING的热门评论
Thank you so much to all the instructors there, for teaching the actual Machine Learning 😃😃 I have learned lot of things from this course and it will surely help in my future,😃🤝
Very good introductory course, I highly recommend it to anyone looking to get a flavour of the methods behind the recent advances in AI without going into super-technical details.
This course give a good introduction toward machine learning and AI. someone who wants to pursue his/her career in ML and AI in future this course would definitely help him/her
Thanks Coursera and Duke University for this course. It is very insightful to get understood the basics of ML and applied ML in numerous fields. It really made me to move ahead with ML domain.