Shypd.aiThe largest open index of AI toolsbasic_model_scratch is an Open Source & Models tool that provides implementations of classic machine learning models from scratch. It allows for benchmarking these models against popular ML libraries like scikit-learn.
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basic_model_scratch is a GitHub repository offering from-scratch implementations of various classic machine learning algorithms using Python, with limited reliance on NumPy and Pandas. The project aims to refresh knowledge and provide a clear understanding of how these models work internally. Users can benchmark these custom implementations against established models from popular ML libraries such as scikit-learn. The repository includes models like Linear Regression, Logistic Regression, Random Forest (Classifier and Regressor), K-Nearest Neighbors, and a custom Neural Network with features like SGD, multiple hidden layers, various activation functions, L2 regularization, and Dropout. It also features PyTorch-based implementations for neural networks, autoencoders, and collaborative filtering, focusing on avoiding high-level PyTorch functions.
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