In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically.
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
This course is part of Deep Learning Specialization
Instructors: Andrew Ng
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4.9
(63,421 reviews)
Intermediate level
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Flexible schedule
Approx. 23 hours
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Assessments
3 assignments
Taught in English
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This course is part of the Deep Learning Specialization
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There are 3 modules in this course
Discover and experiment with a variety of different initialization methods, apply L2 regularization and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model.
What's included
15 videos5 readings1 assignment3 programming assignments
Develop your deep learning toolbox by adding more advanced optimizations, random minibatching, and learning rate decay scheduling to speed up your models.
What's included
11 videos3 readings1 assignment1 programming assignment
Explore TensorFlow, a deep learning framework that allows you to build neural networks quickly and easily, then train a neural network on a TensorFlow dataset.
What's included
11 videos7 readings1 assignment1 programming assignment
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4.9
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NC
5
Reviewed on Aug 18, 2017
Yet another excellent course by Professor Ng! Really helped me gain a detailed understanding of optimization techniques such as RMSprop and Adam, as well as the inner workings of batch normalization.
AA
4
Reviewed on Oct 22, 2017
Assignment in week 2 could not tell the difference between 'a-=b' and 'a=a-b' and marked the former as incorrect even though they are the same and gave the same output. Other than that, a great course
AO
5
Reviewed on Apr 5, 2018
Fantastic course! For the first time, I now have a better intuition for optimizing and tuning hyperparameters used for deep neural networks.I got motivated to learn more after completing this course.
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