simple but efficient kernel regression and anomaly detection algorithms
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Updated
Aug 2, 2024 - MATLAB
simple but efficient kernel regression and anomaly detection algorithms
Certifiable Outlier-Robust Geometric Perception
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Direct and robust methods for outlier detection in linear regression
🇵🇸 PalTaqdeer is an AI-Driven Student Success Forecaster. Was developed for Hackathon Google Launchpad, data analysis techniques, Linear regression model, and Flask for the web 🇵🇸
Projects of Business Analyst Nanodegree Program
[IEEE TKDE 2023] A list of up-to-date papers on streaming tensor decomposition, tensor tracking, dynamic tensor analysis
Toolkit to assist life science researchers in detecting outliers
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A tool for simple data analysis. A rip-off of R's dlookr package (https://github.com/choonghyunryu/dlookr)
This repository contains my learning path of python for data-science essential training(part-1). Here, I have included chapter-wise topics and my practice problems. Also, feel free to checkout for better understanding.
[APSIPA ASC 2022] "Robust Online Tucker Dictionary Learning from Multidimensional Data Streams". In Proc. 14th APSIPA Annual Summit and Conference, 2022.
Techniques to Explore the Data
The dataset is about past loans. The loan_train.csv data set includes details of 346 customers whose loans are already paid off or defaulted.
Predict laptop prices using machine learning. This project leverages multiple linear regression to achieve an 82% prediction precision. Explore the influence of features like brand, specs, and more on laptop prices.
This repository contains clustering techniques applied to minute weather data. It contains K-Means, Heirarchical Agglomerative clustering. I have applied various feature scaling techniques and explored the best one for our dataset
Exercises on Timeseries Decompositions, Monte Carlo Simulations, and Outlier Detection
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