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 faz parte do Programa de cursos integrados Aprendizagem profunda
oferecido por


Informações sobre o curso
Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML
Habilidades que você terá
- 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
oferecido por
Programa - O que você aprenderá com este curso
Practical Aspects of Deep Learning
Optimization Algorithms
Hyperparameter Tuning, Batch Normalization and Programming Frameworks
Avaliações
- 5 stars88,21%
- 4 stars10,60%
- 3 stars1%
- 2 stars0,11%
- 1 star0,05%
Principais avaliações do IMPROVING DEEP NEURAL NETWORKS: HYPERPARAMETER TUNING, REGULARIZATION AND OPTIMIZATION
Everything, Everyparameter in neural networks looks familiar to me now. I feel like I can optimize them for better accuracy. Overall I learned some new things and the way of teaching was really nice.
Excellent course. Bit tougher than first course. For those who have done Machine Learning course earlier and wondered that first course feels almost similar, second course is the 'real' next course.
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
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.
Sobre Programa de cursos integrados Aprendizagem profunda

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