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.
Este curso forma parte de Programa especializado: Aprendizaje profundo
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Acerca de este Curso
Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML
Habilidades que obtendrás
- Tensorflow
- Deep Learning
- Mathematical Optimization
- hyperparameter tuning
Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML
Ofrecido por
Programa - Qué aprenderás en este curso
Practical Aspects of Deep Learning
Optimization Algorithms
Hyperparameter Tuning, Batch Normalization and Programming Frameworks
Reseñas
- 5 stars88,21 %
- 4 stars10,60 %
- 3 stars1 %
- 2 stars0,11 %
- 1 star0,05 %
Principales reseñas sobre IMPROVING DEEP NEURAL NETWORKS: HYPERPARAMETER TUNING, REGULARIZATION AND OPTIMIZATION
Could have increased assignments and some more indepth knowledge of tensorflow and proper installation way of tensorflow cause mine is showing error when iam trying to practice as shown in the video
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.
I have done two courses under Andrew ng and I am grateful to Coursera for their highly optimised and easily learning course structure. It has greatly help me gain confidence in this field. Thank you.
great and practical insight. carefully crafted assignments. still coding in python and the quirks coming with it are sometimes of equal difficulty if not worse than understanding the explained theory
Acerca de Programa especializado: Aprendizaje profundo

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