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).
von
Introduction to Machine Learning
Duke UniversityÜber diesen Kurs
Karriereergebnisse der Lernenden
13%
13%
Karriereergebnisse der Lernenden
13%
13%
Lehrplan - Was Sie in diesem Kurs lernen werden
Simple Introduction to Machine Learning
Basics of Model Learning
Image Analysis with Convolutional Neural Networks
Recurrent Neural Networks for Natural Language Processing
Bewertungen
- 5 stars74,61 %
- 4 stars20,73 %
- 3 stars2,76 %
- 2 stars0,65 %
- 1 star1,24 %
Top-Bewertungen von INTRODUCTION TO MACHINE LEARNING
This is the best course for the Machine Learning! I liked all the instructors, especially, I loved Lawrence Carin Sir's lectures simplified way of teaching! Thank you Team.
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.
Thanks.....
Shivam Tyagi
I felt that I took the best descition in taking this course, because the professors took this course with atmost clarity and made even the difficult concepts understand easily.
Thank you Professors
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