Identifying the Digits using Image Classification

Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.

Performed ETL processes in the cloud to upload a dataframe to an RDS instance and used PySpark to perform a statistical analysis on Amazon datasets.

This is my graduate thesis, a mobile applicaiton with computer vision

A groundbreaking initiative aimed at enhancing the independence and quality of life for individuals suffering from blindness and visual impairment. Navigating the world with limited vision presents numerous challenges, and our project addresses these difficulties through the integration of artificial intelligence and computer vision technologies.

Potato disease classification model

A Website For Farmers To Guide Them Regarding Crop Prouction In Their Native Language

Analyze and predict if a flight will depart on time using airport data.

The purpose of the project is to analyze Amazon reviews written by members of the paid Amazon Vine program using AWS, PySpark, and SQL.

Repositorio con análisis de los data ENAHO de los módulos...

Final Project of Applied AI about text classification on unlabeled data using NLI and BERT

In this project, I have classified product reviews from E-commerce website into positive, negative, and neutral category, with the help of machine learning and Natural language Processing.

Competition Description MNIST ("Modified National Institute of Standards and Technology") is the de facto “hello world” dataset of computer vision. Since its release in 1999, this classic dataset of handwritten images has served as the basis for benchmarking classification algorithms. As new machine learning techniques emerge, MNIST remains a re…

The aim of this project is to develop a robust sentiment analysis system that can automatically classify restaurant reviews as positive, negative, or neutral based on the sentiment expressed in the text.

Python Project: Build a PDF File Handling Tool from Scratch

Data analysis project using PySpark to perform the ETL process to extract data, transform it, connect it to AWS RDS, and load it into pgAdmin. Lastly, performed an analysis via PySpark, Pandas, & SQL to determine biases on reviews.

This repository is dedicated to analyzing and visualizing sentiment patterns in social media data, providing insights into public opinion and attitudes towards specific topics, brands, or entities. The dashboard offers a detailed view of how different entities are perceived online, helping users to gauge overall sentiment and identify trends.

Jupyter NB that contains my final class project for the Summer course MS03: Python Programming for Social Scientists by the ECPR in association with KU Leuven. The main objective of this project is to consolidate my newfound skillset of data, collection, processing and manipulation from different sources such as websites or APIs.

some examples of different terminologies used in ML and DL