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Volver a Custom Models, Layers, and Loss Functions with TensorFlow

Opiniones y comentarios de aprendices correspondientes a Custom Models, Layers, and Loss Functions with TensorFlow por parte de deeplearning.ai

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Acerca del Curso

In this course, you will: • Compare Functional and Sequential APIs, discover new models you can build with the Functional API, and build a model that produces multiple outputs including a Siamese network. • Build custom loss functions (including the contrastive loss function used in a Siamese network) in order to measure how well a model is doing and help your neural network learn from training data. • Build off of existing standard layers to create custom layers for your models, customize a network layer with a lambda layer, understand the differences between them, learn what makes up a custom layer, and explore activation functions. • Build off of existing models to add custom functionality, learn how to define your own custom class instead of using the Functional or Sequential APIs, build models that can be inherited from the TensorFlow Model class, and build a residual network (ResNet) through defining a custom model class. The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models....

Principales reseñas

PK

3 de feb. de 2021

It is advanced TF specialization and the way contents are presented in the course are very systematically. Definitely recommended for developers already familiar with TF and wanted to explore further.

DS

29 de mar. de 2021

I was looking for a course about this specific topics. Previous NN courses were cool, but I think they kep short on making more complex Architechtures, which is perfectly addressed in this course.

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151 - 163 de 163 revisiones para Custom Models, Layers, and Loss Functions with TensorFlow

por mohit d

10 de sep. de 2021

One of the best course on custom Models and layers . As we all know importing a layer is an easier task it just includes a line but making our own models and layers is something which I always wanted to learn and I would like to say this course completely justified it

por Yuqi W

24 de abr. de 2022

The course is overall very good and helpful to help me build my custom Model

Learn a lot of new concepts

But there are also lots of grading error

And I personally found # Your Code start Here# is annoying as I had to delete them first before I can code

por Thierry K

9 de may. de 2022

A little bit too easy. It's too bad that the coding assigments are so easy and don't need any deep thinking...

Nevertheless it's a good course and the instructor explains very well !

por Nakshatra G

30 de mar. de 2022

A little tedious course but overall a great one. I think after going through code some more times the concepts will seem fairly easy.

por David R

3 de may. de 2021

some good stuff, but too short and pretty easy

por JackT T

17 de ene. de 2021

Very nice course!

por Ian S

11 de sep. de 2021

​good course

por José L

15 de abr. de 2021

The content is very clearly presented, but is very easy. Also miss a real-world challenging application exercise. All in all, too short, too easy for an "intermediate" level course.

por Artem M

23 de jul. de 2021

Just an overview straigt from tensorflow documentation without any practical use cases or anything that has more value than completely free youtube tutorials

por Federico C

3 de nov. de 2021

An interesting perspective, but the assignements modalities are a bit too easy.

por Грачев Д И

11 de feb. de 2022

Too easy tasks. This course can be passed in one day easily

por Ann A

5 de ene. de 2021

Simple course. A very simple course. Too simple course. There are very few practical works and they are too simple. There is almost no description of the features of the application of certain techniques. I am disappointed

por Varun S

30 de dic. de 2020

Libraries are not explained properly, looks like its just code walkthrough,