Linkedin Learning – Training Neural Networks In Python
English | Tutorial | Size: 498.72 MB
Neural networks are widely used in everyday applications like online shopping, weather forecasting, and smartphones. This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter.
This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time-all while using a tool that you’ll likely encounter in the workplace. Check out the “Using GitHub Codespaces with this course” video to learn how to get started.
Prerequisites
You must feel comfortable writing code in Python 3.
Project
Build a neural network from scratch using Python.
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