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Отзывы учащихся о курсе Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization от партнера

Оценки: 60,969

О курсе

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. 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....

Лучшие рецензии


4 апр. 2021 г.

Fantastic course and although it guides you through the course (and may feel less challenging to some) it provides all the building blocks for you to latter apply them to your own interesting project.


26 авг. 2021 г.

Amazing course which focus on the theoretical part of parameters tuning, but it needs more explanation of Tensorflow, as I felt a little lost in the last project. Except that, it is an amazing course.

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526–550 из 7,028 отзывов о курсе Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

автор: Malena M

6 янв. 2018 г.

Excellent course. Andrew Ng is an excellent instructor, providing very intuitive explanations to very complex models, and very useful applied advice. Makes the course super accessible to anyone with a basic background in statistics.

автор: said o

30 июля 2020 г.

Awesome course as always ! It is very nice to have a very experienced deep learning practitioner showing you step by step how to build your own models and sharing many tips, intuitions and practices in a such a fluid and clear way.

автор: ONKAR S

30 апр. 2020 г.

Best course from deep learning ai i have learn regularization , different optimization algorithm like rms_prop, momentum and Adam also lean what is deep leaning framewrok and also use one of them in assignment of week 3 of coursera

автор: Angelo C

6 мая 2019 г.

Enjoyed the class and would recommend to those who wants to know more about the hyperparameters relating deep learning. Materials well explained by Prof Ng and assignment equally well designed. Looking forward to the next section.

автор: Sagar K

19 мар. 2019 г.

Liked the content of this course. I would have liked optional videos about the mathematics behind the optimization algorithms. Appreciate the focus on building the optimization algorithms from ground up before learning a framework.

автор: Anand R

23 февр. 2018 г.

A great course. I appreciate the way how Andrew Ng explained all the technical details which i have never able to understand. Before taking this course, it used to be black box for me. Many many thanks to the great teacher of AI.

автор: MARKO Y

6 янв. 2021 г.

Andrew Ng explains everything so well. I am still a high school student without any calculus background yet, and I can still understand all the concepts. I recommend this course to any young individuals getting into deep learning!

автор: Karim K

18 сент. 2020 г.

Nice course on hyperparameter tuning, regularization, and optimization. Those who are research scholars will get deep knowledge. Working professionals get good hints for improving the model and accuracy through various techniques.

автор: Busra N A

19 авг. 2020 г.

I enjoyed the every bit of this course! It is very well structured as always and optimization methods are clearly explained. I like the last programming assigment the most. It gives you a solid grasp of Deep Learning architecture.

автор: Enrico V

25 сент. 2019 г.

Andrew NG is masterful at explaining complex things in the clearest possible way teaching all and only you need to get an understanding of the subject that is good and complete relative to the goals of the course. Amazing teacher.

автор: Eymard P

16 июля 2018 г.

Very well explained and detailed. The less positive aspect is that I think the programming assignements are a bit too easy. But for the rest it's perfect, it's always interesting and clear. Thank you for the high quality content !

автор: Adikwu U S

31 мая 2020 г.

Prof. Andrew did justice to the topic. The course contents are very insightful with respect to how the choice of parameters initialization and optimization techniques could influence the overall outcome of a Neural Network model.

автор: Bharath K

28 сент. 2017 г.

Nuts & Bolts of deep learning were very well explained thought in this course which will be very useful in building a robust neural networks. Maths behind the concepts were explained clearly. Thank you very much Prof.Andrew Ng !

автор: Jingying W

14 июля 2020 г.

This course really helps me understand different optimization functions, regularization and dropout these valuable tools in depth. Implementing Adam and Momentum more or less from scratch makes me feel more familiar with them ;)

автор: Ganesh S

21 июня 2020 г.

Great next step to the First Course. The jump into Tensor Flow was a little sudden and maybe we could've had some more smaller exercises mimicking other problems in Tensorflow before the new one came up for the final assignment.

автор: Carlos A F

19 мар. 2020 г.

The main advantage of this course is the amazing capacity of professor Andrew Ng to facilitate the understanding of key concepts on Deep Neural Networks. The assignments help a lot to improve the comprehension of the concepts.

автор: Jinxiang R

19 мая 2019 г.

I am so grateful that Andrew and his team provide such great course, after completed the course now I have more understanding about different optimizer and regularization methods of the NN. And practical exercise with tensorflow

автор: Rahul v

4 сент. 2018 г.

This course is awesome. In the end of this I can understand the how to make your model more efficient and optimal. How I can play with our training set and how to improve the our Deep Neural Network.

Thank you so much Andrew sir.

автор: Ai-sawan J

2 апр. 2018 г.

I like the way Prof. Andrew explains intuitions and how Momentum works in Deep Learning. Also, this course gives practical explanations of how improve models. I would recommend to anyone who want to start learning Deep Learning!

автор: Dixant M

6 окт. 2017 г.

All the techniques taught were very effective. Before this course, I made a NN without knowing these techniques and it was a pain to get it to converge. Hopefully, after applying these techniques. it is performing very well now.

автор: Anurag D

24 июня 2021 г.

This course is excellent to get a start of deeplearning.

I really emphasize this.

Dr. Ng is an awesome professor who can simplify abstract and complex concepts to a really linear knowledge flow i.e. removed activation layer hahha

автор: Ramin N

11 окт. 2020 г.

This course was very valuable and informative, and I wanna say a special thanks to Dr. Andrew NG, a great professor. Thank you very much, and finally thanks to the Coursera for giving me the opportunity of learning this course.

автор: HE Y

14 июня 2020 г.

This course gives me a comprehensible insight into the tuning of hyperparameters in the Deep Learning. It gives me a better understanding by some useful and practical exercises. I really want to say thanks your efforts, Andrew.

автор: Zongyi G

16 мая 2020 г.

I wish there are exercises for coding back-propagation on Batch-normalization and multinomial logistic regression from scratch (using python and NumPy only). That would help to deepen my understanding of those concepts greatly.

автор: Steve A

25 мая 2018 г.

Good stuff. All in all well worth the few weeks to get a better idea of how to thing and deal with parameters.

I feel like I need a real course on tensorflow though. Documentation and tutorials are not googles strong point.