Tools created for machine learning classification model evaluation

Prediction of students' dropout using classification models. Data visualisation, feature selection, dimensionality reduction, model selection and interpretation, parameters tuning.

Valor is a centralized evaluation store which makes it easy to measure, explore, and rank model performance.

Python tools for the AeroCom project

This repository contains a machine learning model aimed at predicting student performance across various metrics. Utilizing a diverse set of Machine Learning Regression algorithms, the model predicts scores based on demographic and academic variables.This project demonstrates robust approach to leveraging machine learning for educational outcomes.

[ICLR 2024] Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain

"SocialScope harnesses the power of data science to Instagram's vast content, providing insightful analytics and trend predictions for informed decision-making."

Bias detection and contextual evaluation tool for your AI projects

This repository contains code and documentation for a machine learning project focused on predictive maintenance in industrial machinery. The project explores the development of a comprehensive predictive maintenance system using various machine learning techniques.

This repository serves as a comprehensive showcase of my skills and expertise in data science, encompassing various projects and exercises completed throughout the bootcamp.

✨✨Latest Papers about LLM-based Evaluators

Given an image query, the goal is to retrieve the relevant images from CIFAR-10 Dataset.

This repository features code for a fraud detection model achieving 100% accuracy in identifying fraudulent credit card transactions. Utilizing transaction data from Jan 2019 to Dec 2020, the model employs RandomForestClassifier, assessing features like credit card numbers, transaction amounts, and merchant information.

This repository lists one of my projects and findings as part of my Machine Learning DevOps Engineer Nanodegree.

Creating predictive models to classify Trump's vote share and clustering counties based on demographics and economic variables. Report findings in PDF with detailed methodologies, model assessments, and R code for the project.

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.

This repository hosts code for a machine learning-based credit card fraud detection project.

Repositori ini berisi dua project analisis data menggunakan metodologi CRISP-DM. Project pertama meneliti tren penjualan Walmart dengan Supervised analysis menggunakan algoritma Naive Bayes Gaussian dan K-Nearest Neighbors. Project kedua mengeksplorasi faktor sosio-ekonomi antar negara dengan Unsupervised analysis.

Predict sentiment of text as positive or negative using Python's NLTK and scikit-learn.

This GitHub repository contains a comprehensive project demonstrating image classification using TensorFlow and Keras on the CIFAR-10 dataset. The project covers various aspects of the machine learning pipeline, including data preprocessing, model building, training, evaluation, and visualization.