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dbscan-clustering

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Example and analysis of basic machine learning. 1. Logistic Regression and SVM, 2. PCA and LDA, 3. Model Evaluation and Hyperparameter Tuning, 4. Sentiment Analysis, 5. Clustering: K-means, hierarchical clustering, DBSCAN, agglomerative clustering, 6. Feedforward Neural Networks, 7. Deep Neural Network using TensorFlow

  • Updated Mar 1, 2020
  • Python

Introduction to Machine Learning course - Spring 2021 - Supervised and Unsupervised Learning, KNN Classification Models, Naive-Bayes Classifier, Regression Analysis, K-Means and DBSCAN Clustering Analysis, Association Rules and PCA, Confusion Matrix, Normalization, Dummy Variables.

  • Updated Sep 30, 2021
  • HTML

Perform Clustering for the crime data and identify the number of clusters formed and draw inferences. Data Description: Murder -- Muder rates in different places of United States Assualt- Assualt rate in different places of United States UrbanPop - urban population in different places of United States Rape - Rape rate in different places of Unit…

  • Updated Feb 19, 2022
  • Jupyter Notebook

This project focuses on network anomaly detection due to the exponential growth of network traffic and the rise of various anomalies such as cyber attacks, network failures, and hardware malfunctions. This project implement clustering algorithms from scratch, including K-means, Spectral Clustering, Hierarchical Clustering, and DBSCAN

  • Updated Jun 11, 2023
  • Jupyter Notebook

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