/MLAlgorithms

machine learning algorithms implementation

Primary LanguageJupyter Notebook

MLAlgorithms

machine learning algorithms implementation

Implemented:

  • Linear regression
  • Logistic regression
  • Random Forests
  • Support vector machine (SVM) with kernels (Linear, Poly, RBF)
  • K-Means
  • K-nearest neighbors
  • Naive bayes
  • Principal component analysis (PCA)
  • Restricted Boltzmann machine (RBM)
  • t-Distributed Stochastic Neighbor Embedding (t-SNE)
  • Gradient Boosting trees (also known as GBDT, GBRT, GBM, XGBoost)

Installation

git clone https://github.com/parth222/MLAlgorithms 
cd MLAlgorithms
pip install -r requirement.txt