Enron fraud detect classifier using Decision tree algorithm

This contains my implementation of the Decision Tree Classifier. It uses only one hyperparamter - max_depth - to tune the model. I am looking to add more implementations of Machine Learning algorithms here.

ML algorithms in Python

A machine learning project in Python to predict the 2020 Australian Open Winner

Sentiment analysis on Rotten Tomatoes Dataset

Let's find decision on your question.This is a python project in which you have to provide your csv file.It will split data into Train Set and Test Set.It will predict decision on Test set and Give you accuracy.

Vertica-ML-Python is a Python library that exposes sci-kit like functionality to conduct data science projects on data stored in Vertica, thus taking advantage Vertica’s speed and built-in analytics and machine learning capabilities. It supports the entire data science life cycle, uses a ‘pipeline’ mechanism to sequentialize data transformation…

Random Forest Classifier

Implementation of Machine_Learninng Algorithms in simplest way.

A web app that assists doctors in prescribing right medicine to patients in order to avoid drug side effects

Performs decision tree modeling over a given dataset using python

Visual demonstration of Hyperparameter Tuning in a Decision Tree Model using GraphViz and Streamlit deployed on Heroku

Data science project

Study customer leakage of a telephone company using AI and ML techniques

Machine Learning (Training + Internship) by InternshipStdio

LDA(Linear discriminant Analysis) for Wine Dataset in machine learning

Decision tree classifier used to decide whether user should consider buying a new car or rely on cabs and car rentals.

A complete implementation of Decision Trees and ensemble methods: bagging, random forest and Adaboost with all the necessary plots.

This repository consists of folders which include some of the courseworks I have completed in my Data Science MSc at KCL.