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Create Custom Layers in Keras

Learners: 101

Instructor: Amit Yadav

Duration:

This 1-hour long project-based course on Coursera's Rhyme platform will teach you how to create a custom layer in Keras and use it to solve a multi-class classification problem. You will get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed, and you will compare your activation layer with the more commonly used ReLU activation layer. Prerequisites include familiarity with Python programming, neural networks, and Keras. You will be able to access the cloud desktop 5 times and the instruction videos as many times as you want. This course works best for learners based in North America. ▼▲

Course Feature Course Overview Course Provider Discussion and Reviews

Go to class

Course Feature

Cost:

Paid

Provider:

Coursera

Certificate:

Paid Certification

Language:

English

Start Date:

10th Jul, 2023

Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [August 31st, 2023]

Skills and Knowledge:

- Creating a custom layer in Keras
- Building a neural network model using the custom layer
- Solving a multi-class classification problem
- Comparing the custom layer with the ReLU activation layer
- Working with Python, Jupyter, and Tensorflow
- Understanding neural networks and Keras

Professional Growth:
This course on creating custom layers in Keras contributes to professional growth in several ways:
1. Enhanced understanding of Keras: By learning how to create custom layers in Keras, professionals can gain a deeper understanding of the inner workings of this popular deep learning framework. This knowledge can be applied to build more complex and customized neural network models in future projects.
2. Improved model customization: Creating custom layers allows professionals to tailor their models to specific requirements and tasks. This skill is valuable in various domains, such as computer vision, natural language processing, and recommendation systems, where custom layers can be used to incorporate domain-specific knowledge and improve model performance.
3. Problem-solving skills: Through the project-based nature of this course, professionals will develop problem-solving skills by implementing a simplified version of a Parametric ReLU layer and using it in a neural network model. This experience will enhance their ability to tackle complex machine learning challenges and find innovative solutions.
4. Comparative analysis: The course also involves comparing the custom activation layer with the commonly used ReLU activation layer. This exercise helps professionals understand the strengths and weaknesses of different activation functions and make informed decisions when designing neural network architectures.
5. Hands-on experience with cloud-based tools: The course is conducted on Coursera's hands-on project platform called Rhyme, which provides a cloud desktop environment with pre-installed software and data. By working on projects in a cloud-based environment, professionals gain practical experience with cloud computing tools and develop skills that are increasingly in demand in the industry.
Overall, this course equips professionals with the knowledge and skills to create custom layers in Keras, enabling them to build more customized and powerful neural network models. It also provides hands-on experience with cloud-based tools, enhancing their technical proficiency and adaptability in the rapidly evolving field of deep learning.

Further Education:
This course is suitable for preparing for further education. It covers the topic of creating custom layers in Keras, which is a valuable skill in the field of deep learning and neural networks. Additionally, the course assumes familiarity with Python programming, neural networks, and Keras, which are foundational concepts in further education in this field.