M. Alejandro Giraldo's Projects
In this project I used a compilation of Album Reviews Ratings made by Kauvin Lucas at Kaggle to do an Exploratory Data Analysis and answer some questions about the data.
Proyecto realizado con Java y Spring boot
Proyecto realizado en Java en el programa Misi贸n TIC
In this project I used VADER to do a sentiment analysis of an e-commerce retailer. I found that, in general, the store has 48% of positive comments. However, two departments have mostly negative comments, Dresses and Trend. I also made word clouds to see and infer what customers liked and disliked at the store
Proyecto en el que se compara la tasa de cambio oficial con la tasa de cambio no oficial, tambi茅n conocida como D贸lar blue
Python app that uses CrewAI to automize news searching and creation of a F1 newsletter
In this project i used the Naive Bayes algorithm to classify fake news. I got a 93% accuracy, but found that if i increased the amount of training data, the accuracy would decrease
I thins project i uses data from the freeCodeCamp New Coders Survey from 2017 to find the best markets in wich the website should focus to get more users
Streamlit App showing data on my Halo Training
Website que calcula la huella de carbono de un recorrido y la guarda en una base de datos
Python app that uses CrewAI to automize job search and CV generation
In our project we evaluated and plotted the concentration of selected pollutants (converted to the Air Quality Index (AQI)) in several cities. Followed by analysing the impact of Covid19 measures on the AQI by comparison to 2018 and 2019 in order to prove that citizens and local governments can contribute to create a better urban air quality. Afterwards we implemented machine learning algorithms (SARIMAX and Random Forest model) to predict the AQI of the health-damaging pollutants PM10 and PM2.5 by using time as the basis for the SARIMAX calculations and weather variables for the Random Forest model
I used the Naive Bayes algorithm to build a Spam Filter classification using a SMS dataset compiled by Tiago A. Almeida and Jos茅 Mar铆a G贸mez Hidalgo. The algorithm had an accuracy of 98,74%
Twitter bot powered by Gemini API