https://github.com/12danielll/neural_networks_project
The project focuses on analyzing neural activity data to classify neuron types (spiny and aspiny). It integrates unsupervised learning methods (PCA, Autoencoders) and supervised learning models (Logistic Regression, MLP) to build accurate classifiers that effectively analyze neurons' electrical responses.
https://github.com/12danielll/neural_networks_project
2d-and-3d-visualizations autoencoders classifier-evaluation cortical-neurons data-compression gradient-descent high-dimensional-neural-datasets logistic-regression mlp mlp-networks neural-classification neuron neuronal-network pca-analysis perceptron roc-auc stochastic-gradient-descent supervised-learning unsupervised-learning
Last synced: 7 months ago
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The project focuses on analyzing neural activity data to classify neuron types (spiny and aspiny). It integrates unsupervised learning methods (PCA, Autoencoders) and supervised learning models (Logistic Regression, MLP) to build accurate classifiers that effectively analyze neurons' electrical responses.
- Host: GitHub
- URL: https://github.com/12danielll/neural_networks_project
- Owner: 12danielLL
- License: mit
- Created: 2025-01-09T13:35:37.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-09T14:02:18.000Z (9 months ago)
- Last Synced: 2025-01-22T21:18:47.073Z (9 months ago)
- Topics: 2d-and-3d-visualizations, autoencoders, classifier-evaluation, cortical-neurons, data-compression, gradient-descent, high-dimensional-neural-datasets, logistic-regression, mlp, mlp-networks, neural-classification, neuron, neuronal-network, pca-analysis, perceptron, roc-auc, stochastic-gradient-descent, supervised-learning, unsupervised-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 2.93 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0