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).
이 강좌에 대하여
학습자 경력 결과
학습자 경력 결과
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 stars74.69%
- 4 stars20.63%
- 3 stars2.77%
- 2 stars0.63%
- 1 star1.24%
INTRODUCTION TO MACHINE LEARNING의 최상위 리뷰
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.
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,😃🤝
A nice introduction to the concepts of machine learning. However, the material between weeks lack coherence (some topics between week 2 and week 3 are a bit repetitive).
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.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
이 수료증을 구매하면 무엇을 이용할 수 있나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.