Shypd.aiThe largest open index of AI toolsMachine-learning-experiments is an Open Source tool that provides interactive machine learning experiments. It includes Jupyter/Colab notebooks for model training and demo pages to see models in action directly in the browser.
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Machine-learning-experiments is an open-source collection of interactive machine learning experiments, designed for educational purposes and hands-on learning. Each experiment features a Jupyter/Colab notebook, allowing users to understand the model training process, alongside a demo page to observe the model's functionality in a browser. The repository covers various machine learning paradigms, including Supervised Learning (Multilayer Perceptron, Convolutional Neural Networks), Unsupervised Learning (Generative Adversarial Networks), and Recurrent Neural Networks. It supports models trained with TensorFlow 2 and Keras, and provides instructions for local setup, dependency management, and model conversion for web deployment using TensorFlow.js. This project serves as a sandbox for exploring different ML approaches, algorithms, and datasets.
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