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學生對 提供的 Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的評價和反饋

40,668 個評分
4,331 個審閱


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.


Oct 09, 2019

I really enjoyed this course. Many details are given here that are crucial to gain experience and tips on things that looks easy at first sight but are important for a faster ML project implementation


176 - Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization 的 200 個評論(共 4,261 個)

創建者 Peyman G

Jan 24, 2019

this course was amazing. I really enjoyed it

創建者 Chad W L

Jan 24, 2019

very good. maybe a bit more of a deep dive than I was expecting, but great nonetheless

創建者 Terry P

Jan 25, 2019

Very good course and well timed with great ideas.

創建者 Damianos M

Jan 25, 2019

Again, a very structured course with Dr. Andrew Ng being so calm and simple explaining all methods of the course. It was worth my time! Many thanks to the organizers :)

創建者 Haris M

Jan 25, 2019

Pure Gold!

創建者 Jayatu S C

Jan 26, 2019 was tough to manage with office but somehow managed. Andrew and his team are magnificent.

創建者 Hussam K

Feb 19, 2019

Amazing course with perfect teacher

創建者 Gabriel L

Feb 20, 2019

So much practical knowledge packed in 3 weeks of study. Amazing tour de force on the practical aspects of deep learning!


Feb 19, 2019

Very good experience using tensor flow framework for deep learning


Feb 20, 2019

best course ever!

創建者 Dharanidaran

Feb 19, 2019

A must have course to know the effect of Hyperparameter tuning, and a great programming exercise on Tensorflow for Beginner. I highly recommend this course if you want to build accurate models

創建者 Alyssa

Feb 21, 2019


創建者 James C

Feb 22, 2019

Very good course.

創建者 Rajnish C

Feb 21, 2019

wanna know what going under hood , explore this one

創建者 Ahmet

Feb 22, 2019

This is the first time, i have learned how the softmax classification, batch normalization, deep nn with tensorflow works, thank you Prof. Ng.

創建者 Yue

Feb 23, 2019

Gracias, gran curso :)

創建者 陈浩然

Feb 24, 2019

I learned a lot from this course.

創建者 Rohan K

Feb 24, 2019

Phenomenal course on in deep learning

創建者 Jayant R

Feb 24, 2019

I didn't knew much about different optimization algorithms and how they work. This course helped in understanding those concepts. Also leaened how to tune hyperparameters. Now, I am able to read tensorflow codes on net and also able to write basic code. Prof. Andrew Ng is the best. Concepts gets very clear on first time watching video.


Feb 24, 2019

Really learned a lot from this course. Hyperparameter tuning is something I now understand much better

創建者 Afiq S

Feb 25, 2019

Though a little more complex for a Python beginner like me, I find it easy to follow :)

創建者 Armand L

Feb 25, 2019

excellent course

創建者 Emilio J

Mar 20, 2019

El curso está muy bien impartido por Andrew NG y te permite adquirir muy rápido conocimientos sobre los puntos clave para mejorar el aprendizaje con redes neuronales de una forma genérica. La práctica de programación con la plataforma tensorflow de python es muy valiosa, aunque se hecha de menos una mayor profundidad en el uso de las herramientas disponibles de tensorflow y otras utilidades de python para redes neuronales. El curso utiliza como ejemplos didácticos y prácticas la aplicación de redes neuronales al reconocimiento de imágnes, pero estaría bien ampliar los ejemplos con aplicaciones prácticas a otros campos como puede ser un modelado de un proceso físico.

創建者 ChangIk C

Mar 20, 2019

Just like all other Professor Andrew's class, best

創建者 Ayon B

Mar 19, 2019

Good explanation of concepts