Some exemplary projects executed during the SpicedAcademy Bootcamp
it's aim is to predict how many bikes are to be made available in order for the bike rental company to be prepared for rushhour Saturday. Data taken from a kaggle competition
it's aim is to Build a model that can predict tomorrows weather in Berlin as precisely as possible. Requirements are: Matplotlib, numpy, panda, sklearn models; Linear Regression, AutoRegression, Polinomial Features and pacf. Result the model reached an accuracy of 90%
Created a Dashboard with Metabase running an instance with the support of AWS, connecting and uploading data onto remote PostgresDB and then transferring that data to Metabase to execute SQL script for Dashboard visualization.
At its prelimary status an analysis of Instagram's Community Algorithm, for more information access the ReadMe file in the project folder