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Introduction to Machine Learning, Universidad Duke

4.7
64 calificaciones
11 revisiones

Acerca de este 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

por ER

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 SK

Sep 19, 2018

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

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11 revisiones

por Eric Theallet

Apr 18, 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 Noah Ratliff

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 Abdul Majeed

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 Pranav Reddy

Mar 10, 2019

very good for getting started.

por Tami Zargari

Feb 28, 2019

Great Course!

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

por Shukshin Ivan

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 Ulubay

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 KAVADIBALLARI VINEESH

Oct 24, 2018

GOOD COURSE

por Erica Ryan

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 Michael Boerrigter

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.