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Back to Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Learner Reviews & Feedback for Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai

4.9
39,068 ratings
4,150 reviews

About the Course

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....

Top reviews

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.

XG

Oct 31, 2017

Thank you Andrew!! I know start to use Tensorflow, however, this tool is not well for a research goal. Maybe, pytorch could be considered in the future!! And let us know how to use pytorch in Windows.

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226 - 250 of 4,084 Reviews for Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

By Amir K

Jan 18, 2019

To the point and effective!

By Elvis S

Jan 18, 2019

Loved this part of the code... it allowed me to understand more about the optimization and regularization tricks such as RMSprop and Dropout.

By David W

Jan 19, 2019

very thoughtful introduction to various learning optimizer. easy introduction into tensorflow.

it would be better if there is more content on the local optima/saddle point issue.

By Raunak N

Jan 19, 2019

Thanks for such a remarkable teaching

By Mohammed U

Jan 19, 2019

Excellent Support and course materials.

By Fernando G

Jan 19, 2019

Exceptional course! Very interesting and illustrative. Only problem I had was with the Tensorflow notebook.

By Juilee D

Jan 20, 2019

very elegant course, with nicely structured assignments and study material

By Shah M D

Jan 20, 2019

Great Course. This course does explain some optimisation algorithm with quit a good detail. That is a good part of it. Many less courses explain those algorithms at a level of abstraction an undergraduate student needs. Also, it shows the usage of tensorflow, which is used by major practitioners.

By Ajay S

Jan 07, 2019

Really a Great course for the deep learning thanks coursera for prioviding me financial aid for the course and i am able to complete the course with in the time . Thanks a Lot .

By AlexZhao

Jan 08, 2019

Awesome course

By WALEED E

Jan 08, 2019

The course is very useful for being acquainted with tuning hyper-parameters and modern optimization algorithms like momentum, RMSProp an Adam. It is also introducing how to prevent over-fitting efficiently from recent papers in addition to mini batching training data. Although it introduces TensorFlow in a brief way, the overall assessment needs some revision.

By Dhananjaykuamr o

Jan 08, 2019

great course

By Lim K Z

Jan 09, 2019

Really love your interviews with the prominent figures in the AI sphere - very inspiring and insightful. Particularly like the advice given by Yoshua Bengio. Keep it up!!!!

By Syed M H J

Jan 09, 2019

Easily the best course on diving under the hood of how a Neural Network actually works and how to tune to the satisfaction of our results.

A no brainer for sure. The best part the exercises. You MUST do the exercises to understand thoroughly how the systems actually work.

By KimYunSu

Jan 09, 2019

I liked it!

By Aakash G

Jan 08, 2019

Started with some basic tensors... so that's good. However I like how Andrew explains the effect of each hyper-parameter on the models output. Happy learning!

By xuezhibo

Jan 20, 2019

nice

By liuyaqiu

Jan 21, 2019

A good course for deep learning novice.

By 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)

By Caroline K

Jan 21, 2019

Great sequel to course 1 for AI beginners.

By ABHISHEK B

Jan 21, 2019

awesome

By dmitry p

Jan 09, 2019

Good course, just jupyter notebook hangs

By Yannik L

Jan 09, 2019

Excellent

By Loay W

Jan 10, 2019

I liked the Framework choice as TensorFlow and the project was nice!

By 江逸群

Jan 09, 2019

Thanks so much for this course