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).
Offered By
Introduction to Machine Learning
Duke UniversityAbout this Course
Learner Career Outcomes
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Learner Career Outcomes
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Syllabus - What you will learn from this course
Simple Introduction to Machine Learning
Basics of Model Learning
Image Analysis with Convolutional Neural Networks
Recurrent Neural Networks for Natural Language Processing
Reviews
- 5 stars74.61%
- 4 stars20.73%
- 3 stars2.76%
- 2 stars0.65%
- 1 star1.24%
TOP REVIEWS FROM INTRODUCTION TO MACHINE LEARNING
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
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.
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.
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,😃🤝
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