Neural Networks for AI Study Group Sessions - Wolfram U

Overview

Introduction to neural networks and their application in AI using Wolfram Language. Explore embeddings, network architecture and training processes.

Course Overview Perfect for anyone new to the world of AI or those looking to further their understanding, these recorded Daily Study Group sessions provide an introduction to neural networks and their application in AI using Wolfram Language. Explore fundamental concepts such as embeddings, network architecture and training processes.

Gain hands-on experience with the Wolfram Neural Net Framework.Featured Products & Technologies:

Wolfram Language (available in Mathematica and Wolfram|One), Wolfram Neural Net Framework

Syllabus

• Introduction to Neural Networks
Overview of artificial intelligence and neural networks
Basics of the Wolfram Language and its application in AI
• Wolfram Neural Net Framework
Introduction to Wolfram Neural Net Framework
Setting up the environment in Wolfram Language
• Neural Network Fundamentals
What are embeddings?
Types of embeddings and their uses in AI
• Network Architecture
Basic components of a neural network
Common neural network architectures and their purposes
Building a simple network with Wolfram Language
• Training Processes
Understanding the training process of neural networks
Loss functions and optimization
Implementing training in Wolfram Neural Net Framework
• Hands-on Sessions
Practical exercises using Wolfram Language
Building and training a neural network model
Troubleshooting common issues in neural network models
• Advanced Topics
Deep learning concepts
Transfer learning with neural networks
• Applications in AI
Real-world applications of neural networks
Case studies using Wolfram tools
• Conclusion and Next Steps
Review of key concepts
Resources for further study and exploration in AI using Wolfram technologies

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Subjects

Artificial Intelligence