Responsibilities & achievements

Implemented backend web scraper to expand Rentalios web application to display room rental info from Colombia, Argentina, UK using the KNN Algorithm and Python. *Implemented scraping from third party rental room websites, channeling data through an ETL pipeline for cleaning and then storing into Neo4j graph database. *Used Pandas to extract information from csv files, and for data manipulation with Data Frame. Used it to clean the information collected, normalizing the information and complying with the required format. Filled empty fields or invalid with numpy.nan. *Deployed a MYSQL DB instance on AWS RDS for Rentalios scraping, added security group rules, created tables for each site scraped.

Responsibilities & achievements

*Used Jupyter notebook to create a neural network to differentiate dogs and cats as well as adjusting the parameters. *Used libraries such as Numpy, Pandas, Sklearn, Keras and Matplotlib. *Created a neural network from scratch, implemented the necessary functionality so that layers could be created of different numbers of neurons, trained the model and then predicted sets of real images. *Optimized the network by defining the number of layers, the number of neurons, the learning rate and the activation function. *Adjusted the parameters until the prediction got a result greater than 70%. *Used numpy for mathematical operations with vectors, such as dot product, division of vectors, generation of random numbers, etc.

Responsibilities & achievements

*Trained machine learning so it could be able to make predictions with real data. *Generated a Random Forest Regression to predict variables in Keras a neural network and adjusted the number of layers, the activation function, and the number of training epochs.

Responsibilities & achievements

*Created purchase orders automatically for the selected cryptos through the Binance API. *Integrated the CoinMarketCap API to obtain information related to the tokens, it analyzes and displays the cryptocurrencies with the most growth potential.

Responsibilities & achievements

*Designed and optimized a neural network model in Python using Keras. *Implemented the functionality to display all the first rows of the data. *Implemented historical data in an xlsx file, the user was able to train the models that are exported and used to predict variables of interest.

Responsibilities & achievements

*Implemented forms to record data used by the application. *Integrated a MySQL relational database on AWS in the backend. Deployed the MYSQL on AWS database and created the queries to insert new data.