/Data-Science-Machine-Learning-Projects

This Repository Contains different Machine Learning Projects on various dataset. From Exploratory Data Analysis - Visualization to Prediction and Classification..

Primary LanguageJupyter Notebook

Machine-Learning-Classification-And-Regression-Projects

This Repository Contains different Machine Learning Projects on various dataset. From Exploratory Data Analysis - Visualization to Prediction and Classification.

Breast Cancer Predication

  • Dataset used : Click here to download
  • Here I have uploaded 2 versions of this project. Difference between these two versions is Feature Selection based on correlation.
  • Both version contains in-depth insight into Dataset - Exploratory Data Analysis, Visualization and Data Preparation.
  • Also tried various methods for data preparation like handle outliers and data imbalance.
  • Version 1 : This Notebook contains simple method for feature selection based on correlation with target attribute.
  • Version 2 : This Notebook contains logistic regression method for feature selection based on column's accuracy.
  • Able to got ~100% accuracy.

Red Wine Quality Prediction

  • Dataset used : Click here to download
  • Notebook contains in-depth insight into Dataset - Exploratory Data Analysis, Visualization and Data Preparation.
  • This Notebook contains simple method for feature selection based on correlation with target attribute.
  • Tried different algorithms for classification and got ~98% accuracy.

Loan Answer Prediction

  • Dataset used :
  • Notebook contains - Data Preprocessing by Scaling, Transforming into One-hot vectors, Data Preparation for model bulding and Model evaluation.
  • This Notebook contains end-to-end implementation of the projects and used different Classification algorithms.

Customer Segmentation - K-means

  • Dataset used : Click here to download
  • This Notebook contains in-depth explaination of K-means clustering algorithm with it's working visualization on randomly generated dataset.
  • Also, Used K-means to segment customers to 3 different Clusters.

Patient Drugs Prediction

  • Dataset used : Click here to download
  • Notebook contains end-to-end implementation of Decision Tree Classifier with printing tree also.
  • Tree : Click here to view
  • This Notebook contains data preprocessing, model building and model evaluation.
  • Got ~98%+ accuracy.

Nutrition Facts for McDonald's Menu Analysis