Modeltime unlocks time series forecast models and machine learning in one framework
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Updated
Jan 4, 2024 - 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.
Modeltime unlocks time series forecast models and machine learning in one framework
Analysis Pipeline for Single Cell ATAC-seq
🤠 📿 The Highly Adaptive Lasso
subsemble R package for ensemble learning on subsets of data
anomaly detection with anomalize and Google Trends data
R Data Structures and Algorithms, published by Packt
Optimizing a Wedding Reception Seating Chart Using a Genetic Algorithm
This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
Movie Recommendation System: Project using R and Machine learning
A series of articles to get started into the field of Machine Learning with R language
An R Package for Density Ratio Estimation
Intention Mining in Social Networking. It Mines Emotions and polarity for the given keyword . For the keyword it searchers the twitter for the comments and analyzes the results for various events such as Election results, Sports prediction Movie ratings, Breaking news events such as demonetisation and many more. Bayes , Maximum Entropy and Hidde…
Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.
Applying Deep Machine Learning for psycho-demographic profiling of Internet users using O.C.E.A.N. model of personality.
Machine Learning algorithms coded from scratch
This Repository Contains R-Codes executed on various Datasets in RStudio. I Hope This Repository is very helpful for those who are Willing to build their Career in Data Science, Big Data.
Algorithms for creating short forms based on psychometric principles.
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
An implementation of K-Means algorithm in R
Large-scale digital mapping of soil organic carbon content by using machine learning algorithms