Movie Recommendation System: Project using R and Machine learning
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Updated
Nov 4, 2021 - R
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Movie Recommendation System: Project using R and Machine learning
anomaly detection with anomalize and Google Trends data
A Unified Framework for Random Forest Prediction Error Estimation
Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.
📷 Generates Text Analytics using Bag of Words. Upload your data and it will suggest the relevant Newsgroups for you.
A web-based platform for annotating short-text documents to be used in applied text-mining based research.
Parallel Grid Search benchmark - H2O Machine Learning
autoEnsemble : An AutoML Algorithm for Building Homogeneous and Heterogeneous Stacked Ensemble Models by Searching for Diverse Base-Learners
Build a predictive model for the sale prices of homes in a city and explore potential equity issues with the real-estate assessment process
This repository contains the implementation of the research paper tVelloso, E., Bulling, A., Gellersen, H., Ugulino, W. and Fuks, H., 2013, March. Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference (pp. 116-123).
Machine Learning with uncertainty quantification and interpretability
The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.
Scripts and functions for a monitoring of air temperature in Antarctica using MODIS data and machine learning
R script for "E5S_metabolomics_workflow" computation
AWS Machine Learning Client
An R package for determining groups of curves
Binary spam classifier in e-mails. It is based on the classification of text using a Naive Bayesian Classifier. The algorithm was written in R.
Resample, parameter tuning, meta-learning, clustering, and mining algorithms for the purpose of data mining and machine learning.
Miscellaneous statistical/machine learning stuff