Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Machine Learning Articles | 519 | 4 years ago | ||||||||
Monthly Series - Top 10 Machine Learning Articles | ||||||||||
100 Days Of Ml Code | 201 | 4 months ago | Jupyter Notebook | |||||||
A day to day plan for this challenge. Covers both theoritical and practical aspects | ||||||||||
Awesome Ai | 121 | 2 years ago | mit | |||||||
The guide to master Artificial Intelligence (machine learning & deep learning) from beginner to advance | ||||||||||
Free Artificial Intelligence Resources | 49 | 2 years ago | n,ull | mit | ||||||
Welcome, to this Open Source Repository regarding FREE ARTIFICIAL INTELLIGENCE RESOURCE. Get Benefit from the free resources mention & kindly five STAR & FORK this so that it can get maximum Fame so that Everyone can take advantage. | ||||||||||
A Guide To Machine Learning In R | 17 | 4 years ago | R | |||||||
A series of articles to get started into the field of Machine Learning with R language | ||||||||||
Statistical Learning Using R | 16 | 5 years ago | R | |||||||
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. | ||||||||||
Ml Classifier | 10 | 17 days ago | 4 | mit | Jupyter Notebook | |||||
Classify news articles into different categories using Machine Learning | ||||||||||
Trendster | 5 | 6 years ago | Python | |||||||
Galvanize Capstone Project Repo: demystifying the evolution of topics over time. | ||||||||||
Source Code | 4 | 5 years ago | Jupyter Notebook | |||||||
The accompanying repository for all the source code of articles from the ML Endeavours blog. ML Endeavours is a blog dedicated to Machine Learning, a subset of Artificial Intelligence (AI). | ||||||||||
Reproducibleresearchcode | 2 | 4 years ago | mit | C | ||||||
Python code to reproduce our article "Toward faultless content-based playlists generation for instrumentals" |
This is a Statistical Learning repository which will consist of various Learning algorithms and their implementation in R and their in depth interpretation. Below are the links to the implementation and their in-depth explanation of the learning algorithms in R. All the documents below contain the under-lying mathematical concepts explained with respect to a simple case study in R.
Supervised Learning
Model Selection techniques - AIC, BIC, Mallow's Cp , Adjusted R-squared , Cross validation error.
Shrinkage Methods and Regularization techniques - Ridge Regression , LASSO, L1 norm, L2 norm.
Non-linear Regression and parametric models
Non-parametric model - K-nearest neighbor algorithm
Tree based Modelling - Decision Trees
Bayesian Modelling technique : Naive Bayes algorithm.
Ensemble learning - Random Forests, Gradient Boosting , Bagging.
Re-sampling methods and Cross Validation
Unsupervised learning
http://rpubs.com/anish20/polynomialRegression
http://rpubs.com/anish20/Splines
http://rpubs.com/anish20/GeneralizedAdditiveModelsinR
http://rpubs.com/anish20/decisionTreesinR
http://rpubs.com/anish20/RandomForests
http://rpubs.com/anish20/radialSVM