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Avis et commentaires pour d'étudiants pour Introduction to Machine Learning par Université Duke

4.6
stars
175 évaluations
37 avis

À propos du cours

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)....

Meilleurs avis

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 sur 37 Avis pour Introduction to Machine Learning

par 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.

par 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.

par 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

par 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.

par 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.

par 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.

par 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.

par Sameera K

Sep 19, 2018

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

par Tarun Y

Apr 22, 2019

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

par 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.

par KAVADIBALLARI V

Oct 24, 2018

GOOD COURSE

par 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.

par Anurag S

Jan 17, 2020

This course is an eye opener for anyone who wants to step or learn about Machine Learning. It provides various scenarios and the steps which you can apply to current real world problems.

This course is a must for all the beginners.

par 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.

par 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.

par Jin T

Nov 13, 2019

Great course! Once you delve into it, you will love the professor's lecture style and learn some great insight into deep learning topics.

par 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.

par Marcus V C A

Oct 20, 2019

It's a basic course, but an useful one. It give us the fundamental concepts to dive in the subject.

par Tami Z

Feb 28, 2019

Great Course!

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

par Madison S

Sep 19, 2019

Excellent course! Very well organized and explained thoughtfully.

par Santosh G

Sep 14, 2019

It is very good contetnt and begin in Machin learning

par PRADEEP K T

May 14, 2019

Easy to understand about machine learning

par Pranav R

Mar 10, 2019

very good for getting started.

par Nitin S R

Sep 15, 2019

Good ML Learning course

par Akhil K

May 19, 2019

Very Interesting Course