Proseminar Paper about DBSCAN Clustering

Contains solutions to assignments based on core Machine Learning concepts

Evolutionary clustering module for Python for usage with a Twitter streaming module.

Successfully established a clustering model which can categorize the customers of a renowned Indian bank into several distinct groups, based on their behavior patterns and demographic details.

Experimentation on Online Retail Data using two clustering Algorithms to discover distinct groups.

Perform Principal component analysis and perform clustering using first 3 principal component scores

Genetic algorithm that determines the quality of clusters generated by DBSCAN based of general measurement metrics of those clusters, developed in Python using sklearn libraries by Juan Carlos Maldonado Lozano and Javier Bernabé García.

Clustering Analysis is used to analyze the travel behaviors, preferences, and attitudes of New York City citizens.

Online retail customer segmentation using Machine Learning (ML) involves the use of algorithms to automatically identify patterns and groups within customer data. ML algorithms can analyze a large amount of customer data in real-time, and can quickly identify customer behavior patterns that might be difficult for humans to detect.

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

Machine Learning with 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.

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…

An Interactive dashboard is built using Dash and Plotly to visualize accidents that occurred in UK. Further, DBSCAN is used as a clustering algorithm to make clusters of accident locations.

Some code to visualize differences between clustering algorithms

README.md

Clustering of the 7 generations of Pokemon

Semi-supervised Anomaly Detection in a large unlabelled dataset