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.
This course is part of the Deep Learning Specialization
Offered By


About this Course
Learner Career Outcomes
10%
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Skills you will gain
- Tensorflow
- Deep Learning
- Mathematical Optimization
- hyperparameter tuning
Learner Career Outcomes
10%
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Offered by

DeepLearning.AI
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Syllabus - What you will learn from this course
Practical Aspects of Deep Learning
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.
Optimization Algorithms
Develop your deep learning toolbox by adding more advanced optimizations, random minibatching, and learning rate decay scheduling to speed up your models.
Hyperparameter Tuning, Batch Normalization and Programming Frameworks
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.
Reviews
- 5 stars88.25%
- 4 stars10.57%
- 3 stars1%
- 2 stars0.10%
- 1 star0.05%
TOP REVIEWS FROM IMPROVING DEEP NEURAL NETWORKS: HYPERPARAMETER TUNING, REGULARIZATION AND OPTIMIZATION
This was a fantastic course. Andrew Ng explains these concepts so clearly and provides practical examples that enhance the learning. Thanks again. I just loved the course as well as its predecessor.
After completion of this course I know which values to look at if my ML model is not performing up to the task. It is a detailed but not too complicated course to understand the parameters used by ML.
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
Thanks.
I enjoyed it, it is really helpful, id like to have the oportunity to implement all these deeply in a real example.
the only thing i didn't have completely clear is the barch norm, it is so confuse
About the Deep Learning Specialization
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.

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