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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Coursera · deeplearning · 2 HN points · 2 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention Coursera's "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" from deeplearning.
Course Description

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.

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Provider Info
This course is offered by deeplearning on the Coursera platform.
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See also: all Reddit discussions that mention this course at reddsera.com.

Hacker News Stories and Comments

All the comments and stories posted to Hacker News that reference this url.
Dec 20, 2017 · 2 points, 0 comments · submitted by mkagenius
There are several courses in this specialization. Only 3 are currently available for enrollment right now.

You can get the course material for free, but won't be able to get assignments graded.

Below are links for all of the courses.

Course 1: https://www.coursera.org/learn/neural-networks-deep-learning

Course 2: https://www.coursera.org/learn/deep-neural-network

Course 3: https://www.coursera.org/learn/machine-learning-projects

Course 4: https://www.coursera.org/learn/convolutional-neural-networks

Course 5: https://www.coursera.org/learn/nlp-sequence-models

To get the course material, you go to each course link and click on "Enroll". Then look for the "Audit" link at the bottom left of the modal dialog that comes up.

For those who are unfamiliar with coursera or interested in just the videos (and NO certificate) you can enroll in "AUDIT" mode:

AUDIT MODE: http://image.ibb.co/iwm0xF/ng.png

The deep-learning course consist of 5 subcourses:

https://www.coursera.org/learn/neural-networks-deep-learning

https://www.coursera.org/learn/deep-neural-network

https://www.coursera.org/learn/machine-learning-projects

https://www.coursera.org/learn/convolutional-neural-networks

https://www.coursera.org/learn/nlp-sequence-models

The deep-learning course is a different course than the prerequisite machine-learning course:

https://www.coursera.org/learn/machine-learning

forgotmysn
fast.ai also has a quality ML course
supermdguy
I love fast.ai's course, but I also appreciate having a solid and thorough free machine learning course. While fast.ai is good for getting onto the cutting edge of deep learning quickly, it doesn't go through a lot of material that most people in the machine learning industry are assumes to know.
smithsmith
Can the certificate be received by completing the course in audit mode and then paying at the end of the course.
flor1s
Thanks for the links! It seems like you can already browse the lecture videos of the first three courses!
ryanschneider
BTW, if you want to audit, you need to search for each course individually (or click seycombi's links above) and click the Enroll button there, there's no Audit option if you click Enroll on the full Specialization.
jjuel
Thank you for pointing this out! Was looking for the way to just audit it and could not figure it out.
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