返回到 Introduction to Machine Learning

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2,656 個評分

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624 條評論

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)....

KS

2020年8月4日

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.\n\nThank you Professors

NN

2020年11月26日

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.

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創建者 Kartik G

•2019年10月29日

Although the course is great from a theoretical point of view, but it has two major flaws. First, it doesn't provide the fundamentals of Machine Learning but instead directly moves to Deep Learning, although building those concepts from ground up. Also, from a practical point of view, this course is really lacking as there is not a single explanation video on any of the coding aspect of Deep Learning and the videos that even exist just ask us to read through the Documentation to learn the practical aspect.

創建者 Lewis C L

•2019年4月22日

Much weaker than Stanford offerings. Strange buildup of topics for a breezy, but not particular accurate understanding. For example: multiple layers of a neural network is introduced before multiple category classification. Transfer learning is introduced incorrectly. The matrix representation of multiple features of an example with multiple examples is introduced very late in the course. The instructor is conscientious and seemingly knows the material despite using non-standard terminology. One wonders if he is primarily a teacher/researcher and rarely a practitioner. One wonders if Duke is a leader in machine learning research.

創建者 Casper v d V

•2021年1月1日

The course is okay, the teaching is helpful explaining the concepts of machine learning well. The problem is the connections between theory and practice. The assignments in pytorch are completely decoupled from the course materials and not explained very well. They expect you to code a model directly from mathematical theory with poor explanation of the pytorch framework and syntax.

創建者 Anumagalla p

•2020年5月26日

It's really an amazing field to learn new things and from institute is like Amazing to me I've learnt more ...it's not at all boring and we'll will be excited for future experience with you 💯

創建者 Vishesh S

•2021年4月25日

This is very wrong thing that happen to us.Coursera tolds that this course if free due to our 9th birthday celebration.But when the time of claiming certificate .Its shows us to buy a certificate.This is cheating .I hate this app ..

創建者 Guido C

•2019年7月9日

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.

創建者 Michael B

•2018年9月30日

Excellent course. Concepts such as gradient descent and convolutions as they pertain to neural networks are explained without going into the mathematical details but, in my opinion, are explained more intuitively and better, as compared to most other courses. The course does include some ungraded Jupyter notebooks exemplifying key elements of deep learning networks. Highly recommended to 'cement' understanding of neural networks.

創建者 K S S

•2020年8月5日

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

創建者 Nagendhiran

•2020年11月27日

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.

創建者 Abhinav t

•2020年7月3日

A very concise and yet beautifully constructed course for introduction to machine learning for absolute beginner having basic knowledge of probability and mathematics.

創建者 sonic s

•2020年3月31日

Very good introductory course ,very well designed and professors explaination is very easy to understand .Go for it guys !

Happy learning !!!!

Sonic Somanna PK

創建者 Erica R

•2018年10月5日

This was a really great course for understanding the basics of machine learning through a lot of simple but relevant, real world examples.

創建者 Shukshin I

•2018年11月24日

It was great to touch new professional area and to understand its fundamentals. The course gives a broad view on machine learning, so I think now I really understand, what the machine learning is and how to use it in my work and even my political investigations.

創建者 Jonah P

•2019年6月2日

The course is a good balance between learning key concepts and doing coding, the coding being optional. The phrasing of quiz questions and answers were sometimes confusing.

創建者 Eric T

•2019年5月28日

Great course ! Pr Carin is clear enough to make you understand complex concepts like LSTM. The Math, calculus, algenra and prob are not too difficult. I enjoyed to follow this course ! To conclude a good introduction to ML to make you go deeper into the subject

創建者 Fuzail A R

•2020年9月2日

A beginner like me who wanted to learn and expirement with machine learning but didn't know where to start, well this is the best course for you. The learning process is highly engaging and the concepts are explained in a well-refined manner.

創建者 Jeff M

•2020年6月29日

I thought this was a great course to build up an intuitive understanding of a few different machine learning techniques. It is certainly skewed more towards breadth than depth, but this is unavoidable given the short length of the course.

創建者 Abdul M

•2019年4月2日

I have a background in pathology and I wanted to understand how machine learning works so that I can take an active part in the changes within my field and understand what is happening. This course was an amazing experience of learning, for someone like me with no background in calculus or linear algebra.

創建者 Prajwal K

•2021年4月26日

Just learning the course and loved it coz of its depth in knowledge in Machine Learning.

Week 1 covers almost all fundamentals topics and lays the solid foundation to the learner in ML.

Looking forward to enjoy learning this course attentively, complete the assignments.

創建者 jonathan g

•2020年8月9日

The concepts presented are very clear. I understand a little more about machine learning thanks to the course. The support of the concepts using PyTorch was also an interesting aspect in terms of integrating theory and practice.

創建者 K. M k

•2021年5月19日

The course covers all the topic's regarding the machine learning and has an excellent explanation of concepts and the slides are very easy to understand thank you for such a wonderful course !

創建者 Leonardo M P M

•2021年5月12日

I simply loved the course. I've been working with Machine Learning, but I didn't understand much about Deep Learning - this course helped me a lot to get started in this new research area.

創建者 ANKUR O

•2020年5月7日

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

創建者 Riley B

•2019年7月30日

I liked the pace and the tensor flow applications. This should be upgraded to TF 2.0 at some point. Also, I would've appreciated some GAN material.

創建者 Ayse U

•2018年11月11日

I like this introductory course, very good one to start to learn machine learning. I will definitely continue studying and re-watch the videos.

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