This repository houses the accompanying code, notebooks, and resources for various posts published on the PureAI's Substack.
The content within this repository is aimed at providing practical guides, tutorials, and insights into the world of Artificial Intelligence, Machine Learning, and related fields. It's tailored for a wide audience, ranging from beginners to experts.
This repository is organized by blog post titles, each having its corresponding code, data, or Jupyter Notebook.
Mastering Hyperparameter Optimization: Unlocking the Full Potential of Supervised Learning Models with PythonFrom Pixels to Patterns: Exploring CNN Architectures and Image Recognition using PyTorchDecoding AI Decisions: Interpreting MNIST CNN Models Using LIMERecommender Systems with PyTorch. From Data to Decisions: A Journey Through AI-Powered RecommendationsUnderstanding GAN Training Strategies, Ethical Implications, and Building Your First GAN with PyTorchBuilding a Simple Transformer using PyTorch
- Python 3.x
- Required libraries as specified in individual folders
- Some projects require the use of Poetry. Here's a link to the installer.
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Clone the repository:
git clone https://github.com/ermattson/pure-ai-tutorials.git