Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization(으)로 돌아가기

4.9

40,161개의 평가

•

4,268개의 리뷰

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....

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.

Jun 03, 2018

Just as great as the previous course. I feel like I have a much better chance at figuring out what to do to improve the performance of a neural network and TensorFlow makes much more sense to me now.

필터링 기준:

교육 기관: Andrei K

•Dec 13, 2018

Very good. I've improved my knowledge in understanding and tuning! Thanks

교육 기관: Zhaiyu C

•Dec 13, 2018

learnt a lot!

교육 기관: Georgy K

•Dec 25, 2018

A bit challenging in term of number of ideas in such limited amount of time. Very useful anyway.

교육 기관: Emmanouil K

•Dec 25, 2018

Wonderful course! You do not need it but having seen some basic linear algebra and calculus would help.

교육 기관: Tian Q

•Dec 26, 2018

Excellent course. Andrew balances theory and intuition perfectly when explaining a method or an algorithm. He helps me to see not only why something is mathmetically correct, but also why it makes sense intuitively.

교육 기관: dsp

•Dec 30, 2018

Nice overview of different steps for improvement. Very accessible introduction into TensorFlow.

교육 기관: Debadatta B

•Dec 31, 2018

One of the finest. Thank you Andrew Sir.

교육 기관: YIXIANG Z

•Dec 31, 2018

Very good introductory material on regularization and optimization. Also introduction to tensorflow as frameworks is spot-on

교육 기관: Can K

•Jan 01, 2019

This course is helping me a lot. I am an undergraduate researcher.

교육 기관: Christina A

•Dec 30, 2018

great overview on tuning techniques with lots of examples, conveys the intuition behind the different concepts as well as its advantages and disadvantages

교육 기관: Suraj K J

•Jan 01, 2019

Andrew Ng. That's all that needs to be said. Thanks.

교육 기관: Krishna P G

•Jan 02, 2019

Provides good overview of hyperparameters and methods to tune them

교육 기관: Eoghan T

•Jan 01, 2019

Thanks, Prof. Ng!

교육 기관: Beng C C

•Dec 31, 2018

Great course! But I am not too sure why this should be placed in number 2, as I feel that topics such as tuning hyperparameters do not resonate well with someone who is not working professionally or is not very experienced in this field. However, still a great course as I will revisit this course when I gain more experience. I also like the last exercise on Tensorflow as there is a lack of courses on Tensorflow on the Internet, so the last assignment on Tensorflow is the most useful which I have found in the course.

교육 기관: SACHIN S

•Jan 02, 2019

Valuable content :)

교육 기관: To P H

•Jan 01, 2019

Great course

교육 기관: 龚鑫

•Jan 27, 2019

very nice, I learned a lot from that course!

교육 기관: Muralidhar P

•Jan 27, 2019

Really good course for practical purpose... Many concepts I learn from here

교육 기관: Paul F

•Jan 27, 2019

Great learning experience. I'm going to keep going. I want to learn more.

교육 기관: Jesus P

•Jan 28, 2019

Great course

교육 기관: Kaiqiang W

•Jan 27, 2019

Pretty Good！

교육 기관: Pochadri A

•Jan 27, 2019

very good understanding of the hyperparameters for various optimization algos is given, with very good intution.

교육 기관: Manawaduge D

•Jan 26, 2019

Excellent resource for learning deep learning basics and techniques. Clear and intuitive instruction style.

교육 기관: Luca C

•Jan 27, 2019

Knowing this makes the difference. How do you evolve from being a monkey behind a keyboard knowing how to tensorflow a NN to homo sapiens? The concepts provided in this course will make the job.

pros: + workflow to address and optimize your supervised learning problems

+ wide and easy-to-get overview on most essential concepts

+ improves your understanding of NN; those who are already familiar with these concepts might still benefit from this clear and insightfull presentation

cons: - programming assignment will not suffices to give you a sufficient knowledge of tensorflow to make your own applications, you should integrate a bit. (However, mastering tensorflow is not the intention of the assignment).

교육 기관: Gilvandro F d M N

•Jan 28, 2019

great journey into deep learning world