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Вернуться к Нейронные сети и глубокое обучение

Отзывы учащихся о курсе Нейронные сети и глубокое обучение от партнера

Оценки: 64,735
Рецензии: 12,240

О курсе

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....

Лучшие рецензии


Sep 02, 2019

I highly appreciated the interviews at the end of some weeks. I am currently trying to transition from a research background in Systems/Computational Biology to work professionally in deep learning :)


May 31, 2019

I have learnt a lot of tricks with numpy and I believe I have a better understanding of what a NN does. Now it does not look like a black box anymore. I look forward to see what's in the next courses!

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11801–11825 из 12,029 отзывов о курсе Нейронные сети и глубокое обучение

автор: mehdi s

Nov 21, 2019

Very good course. It is quite instructive to go through all the basic steps. It just not always clear on the programming assignment why the code has the given structure until the very end. Giving a bit more explanations a the beginning of the notebook on the global code architecture (even as an optional reading) would quite helpful.

автор: Carlos A M

Nov 22, 2019

I think the course is great but a bit easy.

автор: Adil W

Nov 23, 2019

The explanation is very concise and gives good intuition about deep learning provided learners have strong python commands. Otherwise, you have to spend more time to get understand the code in Jupiter notebook. The guideline in the worksheet is also necessary

автор: Safak B

Nov 24, 2019

coding practices could be more challenging but overall great course!

автор: Tejan M

Nov 26, 2019

It was a Great Course. I learnt a lot. Thank You Andrew Sir

автор: Patrick C

Nov 25, 2019

A little bit too much spoon feeding, but good for the basics.

автор: hernan f d

Nov 25, 2019

Me gustaria que la primer semana el curso fuese tan practico como en las otras semanas, asi se tendria mas fresco el fundamento matematico

автор: Pat B

Nov 27, 2019

The notations for some of the math is more complex than it has to be. Also, concepts such as back prop can be explained in a better fashion. Overall, the course is excellent. One suggestion would be to have math done via reading with explanations in the lectures.

автор: Peter K B

Nov 28, 2019

Lectures were clear and very informative but some parts of the assignment were too straightforward.

автор: Debanjan D

Nov 29, 2019

It is a good intro to neural networks.

автор: Himadri M

Dec 01, 2019

Good overview. Programming assignments are seemed a bit confusing. It will be helpful if we have more printed materials for video lessons summarizing formulas etc.

автор: André S M

Nov 29, 2019

Good course, a bit lacking on explanation in some areas and could have an option to skip some mathematics to those with more advanced knowledge. But a great introductory course and very good for revisiting old knowledge.

автор: 덕형 강

Nov 29, 2019

Actually, At the end of the week4 assignment, L_layer_model problem not worked as expected. There might be some problem.

автор: OMRAN K A A

Nov 10, 2019

The thing that I don't like : math was oversimplified

автор: Vaibhav B

Nov 11, 2019

Great course!

Would surely like it even more if coursera adds more assignments

автор: Ashish T

Oct 30, 2019

it was an amazing experience. Learning neural networking felt like childs play

автор: Rohit S J

Oct 14, 2019

Assignments and Programming exercises were very easy

автор: neeraj k s

Oct 31, 2019

Good int terms of basic understanding.

Hyperparameter selection and feature engineering is what i would like to see more in this course.

автор: 1140325971

Nov 02, 2019

Thank you for your class,but i can't understand the reason of the back propagation.I will continue study hard to find it.

автор: Marn Y T

Oct 17, 2019

I think this course can afford to get deeper into the math behind neural networks. Andrew Ng is an amazing presenter, and the homework is really helpful to use as a guide to building my own neural networks.

автор: Vipin C

Oct 17, 2019

Course was very simple for me, but there was one very good thing is that backpropagation is explained very nicely and if one did their assignment carefully than i dont think they will ever forget the logic and maths behind it.

автор: Michelle B M C

Oct 14, 2019

Great course and great course materials. It's beginnings level, you go from a very simple structure to a L-layer NN, so you can actually understand a NN and its parameters and hyperparameters.

You can also tell they've put a lot of energy and dedication into homeworks - they are quite well structured and facilitate a lot students life.

My only (minor) negative comment would be just that: homeworks are quite easy, bc you can follow their advice and tips from the beginning and, if you get 'lazy', you don't need a lot to complete the tasks, even without having to understand exactly what you're doing. I guess you learn as much as you put an effort on learning ;)

автор: Paul E

Oct 15, 2019

For someone who is a beginner, this was an extremely helpful course. Period. Those who think it was "too simple", it might be the case that it was not the right level for them.

Here are some of the things that worked really well.

First, the assignments were well structured and built on each other. I really loved how scaffolded the notebooks were. Showing an estimate of approx. how many lines of code are needed is a great way to signal to the beginner in terms of how much work is needed. While the amount of code needed to write is small, you need to understand *why* you are writing it, and that takes mental effort.

Second, can't say enough great things about the forums. People are responsive and helpful. I have had more help in this forum than at my formal educational institute where the TAs are not either trained to help or don't want to help or both.

Here are some things I wish the course did better

First, I wish the connection to the larger picture was made through each exercise. One suggestion could be using modular blocks inside the notebooks to show the flow of data as you code. The flowcharts inside the notebooks can use a bit of work -- especially in matching them to the lecture slides.

Second, I wish we had a single page where all the derivations and formulae are provided. It was difficult to sift through different weeks and piece them together.

Overall, really great course! I recommend this keeping in mind the limitations that exist!

автор: Anne H

Nov 04, 2019

I enjoyed to do this lovingly created course. The only disadvantage: The programming assignments did not make me to learn, since I could event copy paste some lines. One does not have to think about much to get done and there has not been any tranfer task at all. That's not helpful for learning I think.

автор: Uğur A K

Oct 19, 2019

It was a good course, though I would like more emphasis on mathematics behind the deep learning. I guess that is what next courses aim to do, more mathematics and ways to optimize our deep learning models.