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

4.7
141 calificaciones
32 revisiones

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 TensorFlow, 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 revisiones

GC

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.

RB

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.

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1 - 25 de 32 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 Sameera K

Sep 19, 2018

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

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 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 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 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 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 Tarun Y

Apr 22, 2019

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

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 KAVADIBALLARI V

Oct 24, 2018

GOOD COURSE

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 Tami Z

Feb 28, 2019

Great Course!

A very comprehensive and clear introduction to the field of ML.

por Pranav R

Mar 10, 2019

very good for getting started.

por Abdul M

Apr 02, 2019

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.

por PRADEEP K T

May 14, 2019

Easy to understand about machine learning

por Upul T

May 17, 2019

Excellent introduction in to machine learning and paced ideally to keep the interest throughout the course. Ignites interest to the field.

por Akhil K

May 19, 2019

Very Interesting Course

por Oscar S

Jun 24, 2019

Excelente

por Aliraza

Jul 02, 2019

Simply Brilliant

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 Antonio R C N

Jul 21, 2019

Amazing course

por Sandeep D D

Aug 24, 2019

Thanks

por Zeeshan L

Aug 24, 2019

Best course

por Santosh G

Sep 14, 2019

It is very good contetnt and begin in Machin learning

por Reena P

Sep 15, 2019

It was a very new topic for me but the video had lucid explanations to make it understand for a beginner like me. Thank you.