Classified images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. The dataset was preprocessed, then trained a convolutional neural network on all the samples. I normalized the images, one-hot encoded the labels, built a convolutional layer, max pool layer, and fully connected layer.

Project 1 as Machine learning Nanodegree

Applied ML algorithms on Income Data to find potential donors for charity

A website that uses Machine Learning to predict the chance of school closing due to snow.

Predicting House Prices in Sao Paulo, Brazil

The finding_donors project is a Udacity Supervised Learning project to find donors for fictitious charity 'CharityML'

The front end of a project for predicting vehicle sales prices.

html, javascript, FastAPI, REST API, Python

A Case Study On The Rising Omicron Cases and Public Sentiment Analysis using Twitter Data

Internship Project

Detecting potential corruption events from public expenditure time-series data

Definitions of the difficulty level of English-language films

Stock Profitability Detector: A Flask web app that predicts stock profitability based on user-input stock symbol and purchase date, utilizing historical price data and logistic regression. Includes a dark mode toggle.

Predicts weather of your city on the basis of input paramters provided.

Final project for the Data Science class at the Marine Academy of Technology and Environmental Science (MATES).

🪙 classification project to predict whether a person will donate to charity organization or not

Unsupervised machine learning project 2: Alcanzando los objetivos de desarrollo sostenible, uso de NLP para clasificación de documentos.

Udacity Self Driving Car Nanodegree Project. Using a convolutional neural network in Tensorflow to detect traffic signs

This Python Notebook was developed for a challenge: whose model is the most performant in predicting apartments' sale prices?