This is the repository for the LinkedIn Learning course Artificial Intelligence Foundations: Neural Networks. The full course is available from LinkedIn Learning.
An artificial neural network uses the human brain as inspiration for creating a complex machine learning system. They can classify millions of sounds, videos, and images, answer our questions, understand our behaviors, and even drive our cars. Neural networks are also the foundation of generative AI.
This course introduces the fundamental techniques and principles of neural networks, common models, and their applications. Instructor Gwendolyn Stripling takes you through the different neural network architectures, their components, appropriate use cases, and best practices for improving neural network model performance. Plus, gain hands-on experience building and training a neural network using the Keras Sequential API, an open-source library that demystifies the design and training of neural networks. If you’re looking to achieve a solid understanding of how to build, train, improve and use neural networks, join Gwendolyn in this course.
See the readme file in the main branch for updated instructions and information.
There are two hands-on challenges for you to try on your own. The files needed for these challenges are lableded "04_07_xxxx" and "05_06_xxxx". You'll see a begin and an extras file for each challenge. Use the begin files to try the challenge on your own. Feel free to reference the end files for the solution and the extras file for added code that you can run for additional functionality.
- To use the files, please clone the repo into your own GitHub account or download the files locally.
- We'll be working in Google's Colaboratory notebooks. You can open the notebook from your GitHub, or you can download the files as a ZIP and upload them from your computer.
Gwendolyn Stripling
Gwendolyn Stripling, Ph.D
Check out my other courses on LinkedIn Learning.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent