Spotify Classification Problem 2023

build a models that predicts whether an individual makes over $50,000 per year.

Jazz solo improv AI

Utilizing Apache Spark & PySpark to analyze a movie dataset. Tasks include data exploration, identifying top-rated movies, training a linear regression model, and experimenting with Airflow.

The feature engineering techniques discussed are - dimensionality reduction(pca), scaling(standard scaler, normalizer, minmaxscaler), categorical encoding(one hot/dummy), binning, clustering, feature selection. These are techniques performed on a dataset consisting of Californian House Prices.

client subsection to a term deposit

Life expectancy data processing

DL projects done in Python

Breast Cancer Detection Using Python

Using Natural Language Processing techniques, to predict diacritics of an Arabic Text.

Liver Tumor Detection using Multiclass Semantic Segmentation with U-Net Model Architecture. CT-Scan images processed with Window Leveling and Window Blending Method, also CT-Scan Mask processed with One Hot Semantic Segmentation (OHESS)

Machine Learning for Business - Market Basket Analysis and Clustering

The primary goal of this project is to convert free users of a financial tracking app into paid members. This conversion will be achieved by building a model that identifies users who are unlikely to enroll in the paid version of the app.

This Github repository contains cross selling of health insurance customers on vehicle insurance product. We have to predict whether a customer would be interested in Vehicle Insurance or not by building a ML model. Exploring Insights/Inferences by performing EDA on the given project data. Finding the high accuracy

Classification task using supervised learning techniques algorithms: k-NN & decision trees

Utilizing Principal Component Analysis (PCA) for insightful feature reduction and predictive modeling, this GitHub repository offers a comprehensive approach to forecasting heart disease risks. Explore detailed data analysis, PCA implementation, and machine learning algorithms to predict and understand factors contributing to heart health.

In this notebook, I'm using this dataset called 'flight-price-prediction', which contains the traveller information.In this notebook, I'm trying to run a dummy variable regression model at first, and after that, I'm trying to build a supervised ML Model with higher accuracy of predation.

Book price dataset analysis and modeling

Welcome to the FIFA Dataset Data Cleaning and Transformation project! This initiative focuses on refining and enhancing the FIFA dataset to ensure it is well-prepared for in-depth analysis. The project involves a comprehensive data cleaning process and transformation of key features to improve data quality and usability.