This section comprises of some of the projects which I have completed on Data Analysis, Web Scrapping, Data Cleaning and Machine Learning.
Heart Failure - Analysis
The relationship between the different features of the heart failure patient included in this dataset namely the distribution of age among the patients, death rate, percentage of male and female patients, variation in the platelets amount, creatinine and sodium level in the blood were analysed. The visualisation of data using matplotlib and seaborn library in python helps us to easily understand a lot better about the dataset.
Walmart Weekly Sales Prediction Model
A (feature engineered and hyper-parameter tuned) machine learning model was trained to predict the department-wide weekly sales for each Walmart store. Initially, linear regression model, ridge regression model, decision trees, ensemble models from Scikit-Learn were trained and the best model was chosen to predict the target column. Also python libraries like Pandas, Numpy, Matplotlib, and Seaborn were used effectively to perform data cleaning, exploratory data analysis and gather insights for machine learning.
Nashville Housing Data - Cleaning
The dataset was downloaded from Kaggle and it consists of home value data for the hot Nashville market. SQL queries were used to clean the data by removing the duplicates, imputing and parsing the address column. CTE's, CONVERT, CAST, PARSENAME, SUBSTRING function etc. were implemented for the process of dataset cleaning.
Tableau Dashboards
Data Visualisation and Dashboards for Projects like Covid19, and Airbnb were created successfully by using Tableau. To view my Tableau Dashboards, kindly check my Tableau Profile by clicking below.