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.

Data preparation on raw data using Python

In this two cluster approaches are used: hierarchical clustering and K-means clustering. It is unsupervised learning technique for grouping related data points which shows same behaviour in the dataset regardless of the outcome.

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

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.

Predictive Modelling for Urban Growth using AI

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

EDA & Data Preprocessing on Google App Store Rating Dataset.

This repository contains the whole process to build a machine learning model using python and also explain the steps to deploy it using Flask web framework.

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