/Machine_Learning_Practice

ML Practice Repository

Primary LanguageJupyter Notebook

Machine Learning Practice Repository

A repository of sample code and notebooks made in the process of learning ML

Topics Covered

  • EDA ( Exploratory Data Analysis )
  • PCA ( Principal Component Analysis )
  • t-SNE
  • Feature Engineering
  • Data Pre-Processing
  • ROC - AUC Curve
  • GridSearchCV and RandomSearchCV

Algorithms Done

  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Naive Bayes (Bernoulii, Gaussian)