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Learner Reviews & Feedback for Neural Networks and Deep Learning by DeepLearning.AI

4.9
stars
122,502 ratings

About the Course

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

NL

Oct 3, 2020

This course helps me to understand the basic concept of Deep Learning. However I think this course should include at least 1 week (or 2-3 videos) about math so learners can have a better understanding

MG

Jul 28, 2020

Pretty well organized with really helpful examples and assignment especially. Definitely made the basis for deep learning algorithms. Looking forward to the next modules and dive deep in this domain.

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4851 - 4875 of 10,000 Reviews for Neural Networks and Deep Learning

By IGNACIO H

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May 18, 2022

Excelente curso!

Se abordan los contenidos en profundidad y al mismo tiempo de forma práctica, permitiendo a los estudiantes aplicar los conceptos desde el inicio.

By Erik H

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Jan 10, 2022

I really like the comprehensiveness the course was going through. Although sometimes I felt a little too carried by the code I had to write in each GRADED Function.

By Priyanshu R S

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Jun 6, 2021

Incredibly explained by Prof. Ng, and a great help from mentors to understand NN. I am really grateful to the team and Coursera for making learning so easy and Fun.

By Aditya K

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May 21, 2021

A great introduction to neural networks. You don't need to know much calculus going in but any pre-existing calculus knowledge will only help you get more out of it

By Ömer B

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Feb 16, 2021

I think this course is really qualified and instructive.

An extremely good course for anyone interested in Deep Learning.

Thanks to Adrew NG and DeepLearning.AI team.

By T A O

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Feb 13, 2021

It was very interesting and full of knownledge course. I especially want to thank Mr Andrew NG for his very clear explanations and instruction. Thank you very much.

By María I M

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Dec 27, 2020

Es un excelente curso de introducción al tema. Andrew sabe con mucha precisión lo que se requiere para empezar y la manera evolutiva de presentarlo. Muchas gracias.

By Gokulan S

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Dec 8, 2020

Excellent course. I am delighted that I got to build my first neural network. I really love the content taught. Working out the calculus part is thoroughly worth it

By Smriti P

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Nov 16, 2020

I am from INDIA.I have never seen such a great mentor who always makes a hard topic so easy as if its nothing.Thanks to Andrew NG and his team for this great course

By Rafael M

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Jul 2, 2020

Amazing course. As expected from Andrew and his team. The course provides a great balance between theory and practice, and the assignments are beautifully designed.

By Hasandi P

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Jun 29, 2020

At the beginning I knew nothing about neural networks. With the systematic and proper lectures I got a clear understanding about neural networks and deep learning.

By Kadija H

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Jun 26, 2020

Excellent balance between the fundamental math/theory of neural networks and practical application. Jupyter notebooks make completing the exercises very convenient.

By vishal s

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Jun 8, 2020

Thanks to Andrew Ng and staff for helping me to build intuition on what deep learning is and inherent methods like feed forward, backward prop and gradient descent.

By Manik H

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May 25, 2020

The assessment part is something which needs a little work in terms of proper grading and less ambiguity w.r.t outputs. Other than that, this is a fantastic course!

By BHUSHAN D

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May 25, 2020

I would say, you can benefits most from taking this Specialization. Thanks for, Its best community in the world to spread the knowledge free of cost.Thanks Coursera

By Abhishek P

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May 24, 2020

It was great to attend classes and learned much about the core concept and for the first time I got the best intuition about differentiation, Thanks for this course

By Christian M N

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Apr 30, 2020

Perfect course if your new to machine learning with no deep mathematical background. If you already work with neural networks, you should finish this in a day or 2.

By Rengim C

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Apr 27, 2020

It can be sound weird but I regularly get up 2 hours earlier now to study/follow this Specialization before work. No class excited and inspired me that much before!

By Anandhapadmanabhan R

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Apr 3, 2020

This course was really helpful I never thought that I could build a model from scratch. Completing this course gave me a lot of insights about how everything works.

By Imran

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Mar 19, 2020

It was a really good course. I should have done many years ago, but still its never too late. It is motivating me to keep learning. Thank you, Coursera and Andre Ng

By Dr F B

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Feb 27, 2020

Great online course, much recommended. The assignments might be more difficult and challenging, that would lead to a better perception of the underlying principles.

By Waleed

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Feb 21, 2020

I must say, I am quite amazed from the material of this course. I believe this is a great course that every Neural Network enthusiast must take.

Thank You Coursera.

By Ahad

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Feb 6, 2020

This course gives a better clarity of mathematics behind Neural nets and the programming assignments are very good, upto the mark.Thanks for creating such contents.

By Namburi S

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Oct 18, 2019

An excellent start to someone who want to master in deep learning. The intuitions provided are very much useful to answer the basic questions of "What, Why and How"