LinkedIn – Deep Learning with Python: Optimizing Deep Learning Models 2025-2

Deep Learning with Python: Optimizing Deep Learning Models. This course teaches techniques for improving the performance and efficiency of deep learning models. Taught by Frederik Nowangang, the course focuses on the practical aspects of machine learning and walks participants through real-world coding exercises. Key topics include data preprocessing, data augmentation, regularization methods to prevent overfitting, optimization algorithms, and hyperparameter tuning. The course is integrated with GitHub Codespaces, which provides a ready-made cloud development environment that allows for hands-on practice without the need for local setup. It includes all the essential tools and is accessible from any device, at any time. To learn how to use this environment, read the relevant section in the course. This course is designed for deep learning enthusiasts who want to improve their hands-on skills.

What you will learn

• Understand the different techniques used to optimize deep learning models.
• Preprocessing and enhancing text and image data.
• Using Python to implement regularization techniques in a deep learning model to reduce overfitting.
• Understand how different optimization algorithms work and when it’s best to use them.
• Using Python to tune the hyperparameters of a deep learning model.

This course is suitable for people who:

• Deep learning enthusiasts looking to improve the performance and efficiency of their models.
• Students and professionals who want to gain practical skills in optimizing deep learning models with Python.
• Anyone looking for a deeper understanding of data preprocessing, regularization, optimization algorithms, and hyperparameter tuning in deep learning.
• People who want to use cloud development environments like GitHub Codespaces for coding practice.

Course details: Deep Learning with Python: Optimizing Deep Learning Models

• Publisher: LinkedIn
• Instructor: Frederick Nwanganga
• Education level: Intermediate
• Training duration: 2 hours and 1 minute

Course headings

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Sample course video

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204 MB