This repository contains machine learning projects of some Kaggle competition and others.
1. Titanic - Machine Learning from Disaster
- https://www.kaggle.com/c/titanic
- Use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.
2. House Prices - Advanced Regression Techniques
- https://www.kaggle.com/c/house-prices-advanced-regression-techniques
- Predict sales prices and practice feature engineering, RFs, and gradient boosting
3. Bank Marketing Analysis
- https://archive.ics.uci.edu/ml/datasets/bank+marketing
- This project deals with the analysis of bank marketing dataset by making use of two different classifiers: Decision Tree and Random Forest. The data is related to direct marketing campaigns of a Portuguese banking institution.
- The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (bank term deposit) would be ('yes') or not ('no') subscribed. The classification goal is to predict if the client will subscribe (yes/no) to a term deposit (variable y).
4. Digit Recognizer
- https://www.kaggle.com/competitions/digit-recognizer
- The goal of the project is to correctly identify digits from a dataset of tens of thousands of handwritten images. The data files train.csv and test.csv contain gray-scale images of hand-drawn digits, from zero through nine. The training data set, (train.csv), has 785 columns. The first column, called "label", is the digit that was drawn by the user. The rest of the columns contain the pixel-values of the associated image.
5. Churn Modelling
- https://www.kaggle.com/datasets/shrutimechlearn/churn-modelling
- It is a binary classification problem. Artifical Neural Network (ANN) has been used in this dataset. This data set contains details of a bank's customers and the target variable is a binary variable reflecting the fact whether the customer left the bank (closed his account) or he continues to be a customer.Based on the data, bank can prevent the execution of their cutomers by providing more services, more facilities, etc.