Open source project for data preparation for GenAI applications

sciblox - Easier Data Science and Machine Learning

Numpy and Pandas are one of the most important building blocks of knowledge to get started in the field of Data Science, Analytics, Machine Learning, Business Intelligence, and Business Analytics. This Tutorial Focuses to help the Beginners to learn the core Concepts of Numpy and Pandas and get started with Machine Learning and Data Science.

EverAnalyzer is my thesis in the Department of Digital Systems of the University of Piraeus. EverAnalyzer is a platform for collecting, preprocessing, processing and analyzing Big Data from the Twitter platform.

This project creates a statistical model to predict demand for loans in each region of the USA based on monthly family income and rental costs. The results are displayed on a dashboard updated periodically with data retrieval.

My side project about Data Scientist

Model for easy facilitation of visa processing and approvals

The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe to a term deposit (variable y).

This project explores a Kaggle dataset to build predictive models for house prices. Includes data cleaning, EDA, feature engineering and model training using ensemble methods.

Agentic data intelligence tool using LangChain & Pandas for automated dataset cleaning, governance, and quality analysis.

Final project for DSCI 100: Developed a KNN classification model in R to predict wine quality using physicochemical properties. Conducted data preprocessing, feature selection, and cross-validation to evaluate model performance.

This project focuses on predicting customer purchase behavior using machine learning models, with an emphasis on feature importance.

Ini merupakan repositori proyek akhir untuk aplikasi LeafNet yang di buat oleh Tim Ampera dari kelas Asimo Kelompok 3 pada program Artificial Intelligence Mastery Program yang di selenggarakan oleh Orbit Future Academy

Machine Learning Engineer Nanodegree, Supervised Learning, Finding Donors for CharityML

Data preparation on raw data using Python

3rd Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Linear Regression & Data Preprocessing

In this project, I developed a basic model to predict house prices based on a single feature: the area of the property. Due to the simplicity of the dataset, I chose a linear regression algorithm for prediction. After training the model, I saved the parameters in a pickle file and deployed the model to a web application using Flask.

Scouting the EPL: Player Clusters in the English Premier League