Chevron Left
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization に戻る

deeplearning.ai による Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization の受講者のレビューおよびフィードバック

4.9
54,263件の評価
6,194件のレビュー

コースについて

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow. After 3 weeks, you will: - Understand industry best-practices for building deep learning applications. - Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence. - Understand new best-practices for the deep learning era of how to set up train/dev/test sets and analyze bias/variance - Be able to implement a neural network in TensorFlow. This is the second course of the Deep Learning Specialization....

人気のレビュー

CV

Dec 24, 2017

Exceptional Course, the Hyper parameters explanations are excellent every tip and advice provided help me so much to build better models, I also really liked the introduction of Tensor Flow\n\nThanks.

NA

Jan 14, 2020

After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.

フィルター:

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization: 176 - 200 / 6,116 レビュー

by Amaranath B

Oct 13, 2019

This is an amazing course , the way they had designed the transition from numpy to tensorflow was amazing. The the concepts of gradient descent with momentum to adam optimizer was great coming from your previous course , I can't express how much this has grounded my understanding. I'm pushing myself to complete the specialization. Thanks a lot everyone !

by Naveen K

Sep 25, 2017

The course if very structured. Can't think of any improvement in course structure. Will like to thank Andrew Sir for this great effort.

As an improvement it would be great if people can be encouraged to solve problems on different dataset on internet such as kaggle. Such sources with other help can be provided as work to do after the completion of Kaggle.

by Daniel V I

Feb 09, 2020

A fine continuing of the previous course in this specialization.

Learning optimization algorithms to improve our parameters' update, how to normalize the inputs at each and every layer, how to prioritize certain hyperparameters over others when testing.

All culminating with Tensorflow, a platform that saves us a lot of time in programming Neural Networks.

by GAURAB B

Jun 19, 2019

Brilliant material altogether.. almost a compulsory course for researchers diving on the ocean of deep learning.. While I was reading papers on deep learning I came across all these terms but couldn't understand it.. Now the picture is pretty clear... Thanks Prof. Andrew Ng for this wonderful effort. I have already recommended this course to everyone.

by zhijun l

Dec 06, 2018

A great course talks about the detail in building Neural networks. With the first course as a foundation, student taking this definitely will get a better understanding on hyperparameter tuning and optimization, in addition on training neural networks. I recommend this course to those who would like to know neural networks more than just the concept!!

by shaila a

Jul 26, 2020

The details covered in the course are very important for pracical use. They are not commonly available on the Internet otherwise. Also, with the new libraries that make the task of coding easier, the knowledge of tuning parameters, of optimizing learning curves, is often overlooked. This course highlights the importance of that knowledge. Thank you!

by Oliver M

Aug 14, 2017

Having completed Udacity 730 on Tensorflow, I found Andrew Ng filled crucial gaps in my understanding. He is not afraid of presenting some maths to build intuition, but he always presents it in a straightforward way. Compare his explanation of Adam optimisation with the source paper on the subject. Andrew boils it down and serves it up beautifully.

by Adail M R

Sep 13, 2017

Once more, Prof. Ng show in his simple style how to tackle the tough subject of hyperparameter tuning, pointing to several techniques and helping us selecting the most appropriate ones for the task at hand. The Tensorflow introduction is also very effective and engaging! Looking forward to advance my knowledge and experience with the next courses!

by Diego A P B

Mar 06, 2018

Hyperparameter tuning and the other techniques seen in this course are not perceived to be the most fashionable areas of machine learning and deep learning. Nonetheless, they are crucial parts, and thus the techniques shown in this course will show you how to save great amounts of time and headache when trying to improve and finetune your models.

by K R

Jun 12, 2020

This course is very helpful in the matter of enhancing the knowledge from the previous course and getting the right intuitions about improving deep learning neural networks.

Thanks to Professor Andrew Ng for making it very clear and easy to understand and giving me the right tools for my Phd research .

I look forward to getting to the next course.

by RUDRA P D

Jun 06, 2020

All the topics are very understandable, the way Andrew sir describe a concepts is just awesome. During the first specialization course i.e Neural Networks and Deep Learning , I was very confused about the hyperparameters tunning (like how to know what to chose). Khan Academy has helped me a lot to understand the underlying mathematical concepts.

by Nestor H

Jun 06, 2018

It was a great course to take. I could grab basic knowledge on TensorFlow and on some optimization techniques. I consider all the optimization algorithms are based on gradient descent, it is just that they tweak some parameters, but they are gradient-descent like algorithms. In summary, Dr. Ng is a genius and it is worth taking all his classes.

by Jay P G

Dec 31, 2019

After knowing the basics of Deep Learning and Neural Networks (From the course 1) , this course explains the crux of improving and tuning of the neural networks and it's parameters and Hyper parameters . And the intro to tensor flow at last was just awesome(not exaggerating it!!!) . Congrats to Andrew and his team for such an awesome course .

by Shivdas P

Dec 24, 2019

This course extends what has been taught in the preceding course, especially the different hyper parameters and optimisation strategies. Getting started with TensorFlow in a complete end-to-end example has been one of the things I was looking for and this course puts all that and many other things into perspective. Thanks Andrew and team !!

by Tamas K

Aug 03, 2019

The course was great, thank you! However, I'm really looking forward using Tensorflow in C++ or Swift. The obscure, untyped nature of Python facilitates cargo-cult habits, creates some mystic fog around the variables (since it's not explicit if e.g. 'cost' is a concrete float or an entire computation waiting to be executed) and error-prone.

by Eulier A G M

Aug 31, 2019

The course is very well structured, most of the topics here is perhaps kind of boring due the lack of real-problems projects, but if you stick to it and learn the concepts, will boost your understanding when using Deep Neural Network Frameworks, such as Tensorflow. That makes creating DNN easy to set, understand and apply to your problems.

by Suhas P

Sep 21, 2017

Introduction to TensorFlow was wonderful. This course has helped me visualize and experience end to end flow of an actual machine learning project that helped a lot. Thanks to Andrew for taking efforts to design the course in a user friendly way. Programming tips are intuitive, helps save your time and allows you to focus more on learning.

by Chandan N

Nov 27, 2019

Great insights into the theory of regularization and famous optimization algorithms like RMSProp and Adam. Helps in developing intuition regarding these algorithms work and implementing them from scratch was pretty rewarding as well.

As usual, Prof Andrew Ng patiently explains the theory and helps in building understanding of the material.

by Saransh M

Aug 20, 2019

Started from the basics but made sure that they provided an in depth understanding of some very important concepts like hyperparameters and regularization will well structured quizzes and interesting programming assignments. Really liked the course and would suggest it to anyone trying to set their feet in the field of ML or Deep Learning

by Shuvayan G D

Jun 16, 2019

This is probably one of the best courses on hyperparameter tuning. Along with Andrew's teaching , the course assignments are just perfect to get the perfect intuition of how optimizers work in the deep learning frameworks , also you will be able to build your own optimizer from scratch after doing this course , though not recommended. : P

by faizy

May 17, 2019

This is an amazing course, it helps me a lot to gain the basic intuition, and the idea behind tunning our model, this course provides understanding basic maths of how we can knob various hyperparameters, which would eventually lead us to a better statistical model in term of both speed and performance... Thankyou coursera ...Thanks Andrew

by Ivan T

Feb 04, 2018

Another great course! Enjoyed it very much. Learned a lot of useful techniques. One thing that could be nice to do is to add references and optional material for students who want to go deeper (i.e. add references to publications related to some technique or a blog page). Looking forward to taking more courses in the Deep Learning series!

by Jonah N

Jun 04, 2018

The course really gave me insight into some of the optimization methods that are commonly used. It also helped me to get a better understanding of Tensorflow. I think y'all have done a good job presenting the information with just the right amount of math and explanation. I have recommended this course series to multiple friends already.

by Arpit B

Sep 11, 2017

Thanks Andrew, As always you have been a superb teacher, I am very happy with the content of the course.

One suggestion is to increase the level of difficulty in assignments. Or you can have one more course to develop an difficult deep learning application from scratch, through which we can all apply the concepts and tricks you explained.

by Zihao Z

Apr 25, 2020

It is really helpful to NN rookies like me. I have learnt a lot of important concepts and skills, such as hyperparameters tuning and variables initialization. More importantly, I gain some basic knowledge about Tensorflow, which is a widely used NN framework. I really appreciate the step-by-step instructions in the notebook assignments.