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).
- 5 stars74.71%
- 4 stars20.61%
- 3 stars2.75%
- 2 stars0.65%
- 1 star1.25%
來自INTRODUCTION TO MACHINE LEARNING的熱門評論
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.
very helpful course and all teachers are very expert and their teaching method is also simple but very helpful. I'm happy to take this course.
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
Thank you so much! This course is so amazing and more knowledge to know about how important or importance of machine learning.Thank you so much for this course you offer.