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Opiniones y comentarios de aprendices correspondientes a Introduction to Machine Learning por parte de Universidad Duke

4.6
estrellas
879 calificaciones
210 reseña

Acerca del Curso

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)....

Principales reseñas

KS

Aug 05, 2020

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

AP

May 26, 2020

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 💯

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1 - 25 de 210 revisiones para Introduction to Machine Learning

por Lewis C L

Apr 22, 2019

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.

por Sonic S P

Mar 31, 2020

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

Happy learning !!!!

Sonic Somanna PK

por Erica R

Oct 05, 2018

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

por Kartik G

Oct 29, 2019

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.

por Michael B

Sep 30, 2018

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.

por Eric T

May 28, 2019

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

por Shukshin I

Nov 24, 2018

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.

por Abhinav t

Jul 03, 2020

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

por Jeff M

Jun 29, 2020

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.

por jonathan g

Aug 10, 2020

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.

por Anumagalla p

May 26, 2020

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 💯

por Guido C

Jul 09, 2019

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.

por Ankur O

May 07, 2020

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

por Riley B

Jul 30, 2019

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.

por Ayse U

Nov 12, 2018

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

por Sameera K

Sep 19, 2018

Very Good course explaining the theoretical concepts related to deep learning . Thank you

por Tarun Y

Apr 22, 2019

A very fine tuned Course,used as a warm up course for deep learning,highly recommended

por Noah R

Apr 05, 2019

Great course for beginners, did a lot to fill in the gaps in my knowledge. There could be a little more help with the actual coding parts of the project, the work done in ipython notebook is largely self-taught.

por Jonah P

Jun 02, 2019

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.

por KAVADIBALLARI V

Oct 24, 2018

GOOD COURSE

por Aimee M

May 20, 2020

I was an engineering major at Duke, but never took any sort of computer science/machine learning classes because I didn't have time. This class was super straight forward. Everything just made sense. I don't know how to say it other than that. It was great to see how much of the math and signal processing things I learned could be applied to something like machine learning. Before this class, I had no clue what machine learning was, and now I feel like I understand the main gist and the basis for all of the math behind it.

por Remi C

Jul 19, 2020

Very nice introduction to machine learning with great exemples and teachers. Each lab time (1h each) was overly underestimated in my case for a newbie, 1h would translate into half a day or a full day. And I think a lot more could be explained about PyTorch coding exemples given in the labs, like the choices for filter size dimensions, but overall it was doable.

por Sanjana G

Jun 24, 2020

Really well explained! It was very interesting to learn and as it was from the start it was easy to understand as well. Just one suggestion for the programming assignments also provide the solutions and explain how the coding have been done as understanding that is a bit difficult. Else it was a great course and i really loved it.

por Girish C

May 08, 2020

Really enjoyed the course - it was a bit heavy and required getting used to (also this was my first time doing a course online) but the course has a nice rhythm and it was excellent once i got the hang of it. Very useful course to get an insight into the world of Machine Learning and to increase curiosity and interest.

por Abhik B

Jul 03, 2020

Extremely well structured course. The instructors are knowledgeable and their teaching method is easily interpretable. The course mainly focuses on ML algorithms and how they function , without going too deep into the mathematics , although some mathematics knowledge is surely required before taking this course.