Library for easy deployment of A-Connect methodology.
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Aug 26, 2022 - Python
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regularization-techniques
Here are 7 public repositories matching this topic...
Smooth Effects on Response Penalty for CLM
penalized-regression ordinal-regression categorical-data proportional-odds-regression regularization-techniques
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Nov 25, 2024 - R
Your all-in-one Machine Learning resource – from scratch implementations to ensemble learning and real-world model tuning. This repository is a complete collection of 25+ essential ML algorithms written in clean, beginner-friendly Jupyter Notebooks. Each algorithm is explained with intuitive theory, visualizations, and hands-on implementation.
machine-learning simple machine-learning-algorithms polynomial-regression gradient-descent-algorithm stochastic-gradient-descent classification-algorithm batch-gradient-descent mini-batch-gradient-descent regression-algorithms simple-linear-regression lasso-regression-model lasso-regularization ridge-regression-model multiple-linear-regression-model regularization-techniques regression-metrics classification-metrics ridge-regularization
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Jul 22, 2025 - Jupyter Notebook
This repository implements a 3-layer neural network with L2 and Dropout regularization using Python and NumPy. It focuses on reducing overfitting and improving generalization. The project includes forward/backward propagation, cost functions, and decision boundary visualization. Inspired by the Deep Learning Specialization from deeplearning.ai.
deep-learning gradient-descent l2-regularization performance-optimization model-training regularization-techniques neural-network-architecture overfitting-prevention dropout-regularization
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Feb 19, 2025 - Jupyter Notebook
Regularization is a crucial technique in machine learning that helps to prevent overfitting. Overfitting occurs when a model becomes too complex and learns the training data so well that it fails to generalize to new, unseen data.
numpy inline pandas seaborn matplotlib regularization l1 generalization l2 overfitting regularization-methods overfitting-reduced regularization-techniques regularization-to-avoid-overfitting overfitting-prevention
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Sep 8, 2024 - Jupyter Notebook
This project compares the effects of Ridge (L2) and Lasso (L1) regression models on clinical data.
ridge-regression hyperparameter-tuning l2-regularization lasso-regression regression-analysis feature-importance l1-regularization parameter-optimization regularization-techniques diabetes-dataset feature-importance-analysis
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Feb 21, 2025 - Jupyter Notebook
Classification Using Logistic Regression by Making a Neural Network Model. This project also includes comparison of Model performance when different regularization techniques are used
neural-networks logistic-regression l2-regularization classification-algorithm l1-regularization regularization-methods regularization-techniques
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Jan 20, 2022 - Jupyter Notebook
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