返回到 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

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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....

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.

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.

篩選依據：

創建者 Mushfiqur R

•May 03, 2020

It was a good course on understanding various hyper-parameters, some regularization method, optimization of algorithms, various gradients and gradient checking, batch - mini batch, exponentially weighted average , some tuning algorithms and finally a small introduction to deep learning frameworks. RECOMMENDED!

創建者 Vinodh R

•Nov 12, 2017

The course content was excellent. The only issue is that there were some glitches with the grading of the second week programming assignment, in that I could obtain the expected output, but with repeated submissions, there would be (different) sections which could not be graded due to unnamed technical issues.

創建者 Muhammad A k

•Apr 06, 2020

5/5.Thank you sir for helping me in my career.I recommend everyone to go through this course if you really want to learn detail about hyper parameter tuning , optimizers and regularization used to make neural network better. It helps to open black box of Neural network and know in detail about how all works.

創建者 Renato L

•Jul 03, 2019

Excellent content and very well explained. Thanks for this amazing course.

The course cover the building blocks of a Neural network. Andrew (and his team) did a great job by organizing the content in an evolving way in which you have the chance to build the knowledge from each piece of a (deep) Neural Network.

創建者 Bryan H

•May 28, 2018

Practical programming lessons, and well-paced enjoyable lectures.

Comments:

Move tutorials on TensorFlow to Course 3, which was the most obscure part of the course. TensorFlow isn't as intuitive as other numerical toolboxes, so spending more time on the foundations of TensorFlow might reduce the learning curve.

創建者 Mojtaba H

•Feb 11, 2020

It covers very good tips and tricks to build and enhance deep learning model.

Andrew is the best teacher for ML and Deep Learning, he covers all theory and practice simultaneously.

In this course you can understand all mathematical intuitions and implementation of neural network from scratch by your own codes.

創建者 Shrikrishna B R

•Jul 17, 2020

It is a very good follow up course in this Specialization. It is about how we can improve our a accuracy/predictions by tuning hyperparameters, using better optimization techniques and it also talks about deep learning frameworks. Overall it was a good course. Thank You Andrew Ng for this wonderful course.

創建者 Juan C B

•Mar 08, 2020

Good second course to understand how we can improve our deep learning models with a good hyperparameter selection, some regularization techniques to reduce overfitting such as dropout, l2, early stopping and some optimization techniques for when we have a large datasets like momentum, RMS prop, adam, etc..

創建者 Rob v P

•Oct 02, 2017

This second course in the specialization is really great. I have gained a lot of insight in hyperparameter tuning and the reason why they work (or don't ;-). It is much easier now to understand what models are doing and why we need certain techniques. This is again one of the best courses for deep learning.

創建者 Abdallah D

•Feb 03, 2020

Fantastic course providing a broad overview of hyperparameter tuning in deep neural networks. The introduction on TensorFlow is informative. Looking forward to the three remaining courses of this great specialization on machine leaning. Thanks Andrew and their assistants for putting those courses together!

創建者 Daniel R B

•Jun 06, 2018

I really liked the course. The forum is very helpful navigating programming errors during the assignments.

A thing to improve would be to get the feedback from the forums to the lectures. Specially in corrections that should be made to the programming assignments that don't match the expected result. Thanks

創建者 Steve S

•Dec 11, 2017

Provided a lot of deeper insights passed over in the previous course in the specialization. Between this course and the previous course, you feel like you have a very solid beginner's understanding of deep learning, but one that is also practical enough and comprehensive enough to start coding on your own.

創建者 Marcin G

•Oct 15, 2017

Andrew Ng is a great teacher and will get you excited about improving deep networks. In this course you will get to know how to increase performance of your network. Essential course for deep networks specialists and amateurs. Additionally you will get to know most influential people befind the technology.

創建者 Shashank S S

•Jul 08, 2019

All possible area of Improving Deep Learning models got covered in detail. I liked the lucid and intelligible way of explanation . Since the topics were vast to cover , I would recommend to get the course extended by 1 week with one more programming assignment on using tensor-flow with a capstone project.

創建者 Vincenzo M

•Sep 11, 2017

This course will becoma a foundamental course for people that aim to work in the machine learning / deep learning area because it presents clearly the recent innovations in the deep learning. For production environment people will probably use open source framework, but this course clarify what is behind.

創建者 Joshy J

•Oct 03, 2019

Excellent course if you are passioned about Deep Learning. Walk you through the most basics on how to tune the model parameters so that you can reach the highest accuracy for the model. The lecture is simple and well ordered. The TensorFlow introduction part is more exciting. Overall a wonderful course.

創建者 Dimitrios L

•Feb 18, 2018

Excellent course! Not only does it address critical deep-NNs training issues providing a clear exaplanation around why these tunings are needed, but also provides some empirical advices (e.g. on level of importance on the hyper-parameters, typical values etc) that can be valuable when training depp NNs.

創建者 Aaron B

•Oct 28, 2018

The only thing I wish for is a 'live chat' when an instructor is available, a IRC/slack/chat room for students to help each other, or faster response time when posting to the forums. Also the forums are a bit clunky (I don't remember all the reasons why), but the search allowed me to find useful posts.

創建者 Shashank M

•Oct 10, 2018

This course offers a very quick introduction to methods that could be used to improve usage of deep nets from a practitioner's perspective. Although the mathematical details are not covered in depth, the material furnishes concise list of topics that could be researched upon for in-depth understanding.

創建者 Sachin G W

•Dec 11, 2018

Amazing course, starts right off the bat with hyperparameters, regularization and tunings.

Studied about various optimization algorithms and normalization alongwith mini batches, also the TensorFlow framework.

Thank you to everyone involved in making this course. I highly appreciate what you've made us.

創建者 Muhammad s k

•Dec 03, 2019

I always held an opinion that highly qualified instructors, specifically those holding doctorate degrees are not the good teachers because they can't teach students at their levels. But Sir Andrew Ng proved me wrong, he is a wonderful teacher and tries to explain the minute details.

Salute to you sir.

創建者 Edoardo S

•Jan 20, 2019

Very impressive course, really well done and interesting. One suggestion: apart from the modelling part in the programming assignment, I would also introduce some coding about the computing of the results and the final cost plot (in all the programming assignment these parts are already pre-compiled)

創建者 Shabie I

•Feb 18, 2018

Concepts buried deep in technical jargon and seemingly complex mathematical notation are laid out bare for everyone to understand.

Mr. Andrew Ng is a very special teacher. The humility and down-to-earth character also add immense value to the course. He makes you believe truly that you too can do it.

創建者 Brandon E

•Sep 26, 2017

An excellent continuation of the series. I particularly liked the in-depth discussion of Adam's optimization and the introduction to TensorFlow at the end of the course. The course does a great job of targeting specific concepts with practical advice related to tuning and optimization on real models.

創建者 Kwan T

•Sep 28, 2017

It is amazingly rewarding to learn from Andrew, who is able to articulate so much insights into so many complicated refinements of Deep Neural Networks from so many different research papers. The Tensorflow programming assignment is one of best tutorials I have seen. Thank you for your great effort.