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

26,241 calificaciones
2,950 revisiones

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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....

Principales revisiones

por 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.

por PG

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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2,900 revisiones

por Satyam Dhar

Dec 12, 2018

Yet another great course from Prof. Andrew Ng and Coursera. Deeply grateful to all involved in the preparation of this course. Absolutely essential to learn these concepts if we want to build and optimize deep neural networks for creating great products!

por Manuel Humberto Chagas Baptista Dias

Dec 12, 2018

This course guides you through the details required to finetune your learning algorithms.

por Sagar Joshi

Dec 12, 2018


por 侯宇翔

Dec 11, 2018


por Thitipon Satthaporn

Dec 11, 2018

Parameters tuning is ok to follow, it would be easier if you have numerical methods basics. But Tensorflow is not easy to deal with. Maybe it need a separated course. I will get through to programming assignment again to understand it clearly with tensorflow manual pages.


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.

por Oleksiy Simkiv

Dec 11, 2018

A small validation output error that is still not fixed prevent to rate all stars for the exellent course.

por 黄怡欣

Dec 11, 2018

very good

por 김연희

Dec 11, 2018

좋은 강좌입니다. 단 한글 번역 부분에 오류가 많습니다. 이후에는 수정되었으면 좋겠습니다.

por LeslieJ

Dec 10, 2018

thanks all