yogesh-sidhwani / machinelearning

Machine-Learning-Example-with-Jupyter-notebook

ABOUT

Basic machine learning examples to calculate the accuracy of different filters/Classifiers in predicting IPL winner.

Prerequisites

Python 3.6 Python libraries like numpy, pandas, matplotlib ML library scikit-learn Jupyter

System Setup

Setup a Virtual env Install Virtual Environment

pip install virtualenv Create Virtual Environment

virtualenv -p python3.6 Activate Virtual Environment

source /bin/activate

Data

The root folder contains matches.csv and deliveries.csv.

Start Project

Run jupyter notebook from inside the project root.

Description

The major focus is on Data Analysis and Feature Sampling using different PreProcessors. Model1 - Predict Match Winner using only matches.csv. Model2 - Predict Match Winner using both matches.csv and deliveries.csv. Model3 - Predict any target using both of the data files. The slides.html for different model in code slides folder is created using slideshow in Jupyter notebook. Check Presentation in ppt folder for furter reference