Creating Custom Callbacks in Keras
This 1.5-hour long project-based course on Coursera's Rhyme platform will teach you how to create a custom callback function in Keras and use it during a model training process. You will learn to write a log file, plot the training metrics in a graph, and reduce the learning rate during the training with each epoch. With pre-configured cloud desktops containing all the software and data you need, you can focus on learning without worrying about the setup. Prerequisites include familiarity with Python, Neural Networks, and the Keras framework. This course is best suited for learners based in North America. ▼
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Course Feature
Cost:
Paid
Provider:
Coursera
Certificate:
Paid Certification
Language:
English
Start Date:
17th 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 custom callback functions in Keras
- Writing log files during the training process
- Plotting training metrics in a graph during the training process
- Reducing the learning rate during the training with each epoch
- Python programming
- Neural networks
- Keras framework
Professional Growth:
This course on creating custom callbacks in Keras contributes to professional growth in several ways:
1. Enhanced understanding of Keras: By learning how to create custom callbacks, you will gain a deeper understanding of the Keras framework and its capabilities. This knowledge can be applied to various other projects and tasks involving Keras.
2. Improved model training process: The course teaches you how to write a log file, plot training metrics, and reduce the learning rate during the training process using custom callbacks. These techniques can greatly enhance the efficiency and effectiveness of your model training, leading to better results.
3. Practical hands-on experience: The course is project-based and conducted on a hands-on platform. This means you will gain practical experience by working on real-world projects in a simulated environment. This experience is valuable for professional growth as it allows you to apply your knowledge and skills in a practical setting.
4. Familiarity with cloud-based tools: The course is conducted on Coursera's hands-on project platform called Rhyme, which provides pre-configured cloud desktops with all the necessary software and data. By using this platform, you will become familiar with cloud-based tools and gain experience working in a cloud environment, which is increasingly important in many professional settings.
5. Prerequisites and advanced knowledge: The course assumes familiarity with Python, Neural Networks, and the Keras framework. By taking this course, you can further strengthen your understanding of these concepts and build upon your existing knowledge. This can be beneficial for career advancement and pursuing more advanced projects or roles in the field of machine learning and artificial intelligence.
Overall, this course on creating custom callbacks in Keras offers practical skills, deeper understanding of the framework, and hands-on experience, all of which contribute to professional growth in the field of machine learning and AI.
Further Education:
This course is suitable for preparing further education. It covers the topic of creating custom callbacks in Keras, which is a valuable skill for further studies in machine learning and deep learning. Additionally, the course assumes familiarity with Python, Neural Networks, and the Keras framework, which are foundational knowledge for further education in these areas.
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