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Neural Networks and Deep Learning, deeplearning.ai

4.9
52,127 calificaciones
9,956 revisiones

Acerca de este Curso

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago. In this course, you will learn the foundations of deep learning. When you finish this class, you will: - Understand the major technology trends driving Deep Learning - Be able to build, train and apply fully connected deep neural networks - Know how to implement efficient (vectorized) neural networks - Understand the key parameters in a neural network's architecture This course also teaches you how Deep Learning actually works, rather than presenting only a cursory or surface-level description. So after completing it, you will be able to apply deep learning to a your own applications. If you are looking for a job in AI, after this course you will also be able to answer basic interview questions. This is the first course of the Deep Learning Specialization....

Principales revisiones

por JP

Feb 12, 2018

I would love some pointers to additional references for each video. Also, the instructor keeps saying that the math behind backprop is hard. What about an optional video with that? Otherwise, awesome!

por AG

Mar 07, 2019

I understand all those thing which you have discussed in this course and I also like the way first tell story of concet and assign assignment. Now I fall in love with neural network and deep learning.

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9,753 revisiones

por Michael Fogel

May 19, 2019

Very good and helpful course, glad I did it and I'm going to continue in the series.

My one criticism would be I think the programming exercises were kinda easy... too much starter code was already there. I think I would have learned more had I just been given function signatures and let me sink or swim from there.

por Jaime Moreno Mateos

May 19, 2019

Straight to the point, good balance of theory and practice with additional references given to explore further. Andrew is an extraordinary lecturer, a master on providing quick intuition and progressively build a deeper understanding.

por Jan Kapała

May 19, 2019

This course is the very best resource for learning about DL that I have found. Both lectures and auto-graded assignments are amazing.

por Kanaka Srinivas Chikkala

May 19, 2019

Excellent course for beginners, essential (theory) concepts are explained well and assignments are useful.

por Arturo Victoria

May 19, 2019

Muy buen curso, te da la base para entender como funcionan las redes neuronales.

por Raghunath Utpala

May 19, 2019

This course was very helpful in understanding logistic regression and deep learning.

por Agus Cipriano

May 19, 2019

Excellent course with covers teorycal and practical aspects of NNs

por Willian Henrique Briotto

May 18, 2019

Very technical and explained course to learning the concepts and practice with Neural Networks

por Krishna kumar Natarajan

May 18, 2019

I admire Professor Andrew Ng's patience in helping the students take baby steps by painting a big picture from each small pixel, just as how a neural network is built.

This course has given me great exposure to how neural network, although I realize I need to take a Python course to type code more freely and easily.

I'm going to do that next and then come back to the remaining courses in this specialization.

feedback - it's really hard to visualize some of these matrices and their dimensions used in a large neural network with so many parameters such as nx features, m training examples, n iterations, L layers with (nL, NL-1) weights, (nL,1) biases etc. I understand it's hard to show these matrices by writing as they are very large. I wish someone would develop a more "animative" way of illustrating these matrices that will make the intuition more stronger. for example, calculating forward_activation for all layers and all neurons across these layers by just passing X and parameters is a massive operation and the intuition stumbles purely by the scale of such a matrix operation.

por Eugene Yakshin

May 18, 2019

The course provides a nice hands-on experience with simple deep networks and gives some basic fundamental understanding of this area.

However:

the audio quality is poor, this is especially important because of Andrew's voice timbre

the programing level (from the architectural point of view) is average to say the least (which is especially bad for people without the programming experience - they learn to write bad code right from the start)

video/audio editing is very sloppy in general.