Hi, my name is Emmanuel
an aspiring Software Engineer based in New York.

The app integrates Google Cloud Platform's Firebase infrastructure (Authentication, Firestore Database, Realtime Db, and Storage). So the user can create, update an account and make some posts, and it is all stored in the database to which you can see the video by pressing the See Live button down bellow. So I used HTML, CSS, and ReactJS for the front-end. In addition, SemanticUI and Bootstraps enrich the user experience through sharp UI design, animations, etc.

A simple blog (inspired by Meta Platform’s social media app Instagram) allows users to create and modify an account, post I mages, comment on them, and like them. I used Google Cloud Platforms’ stack, so the Firebase infrastructure for the backend and database. Various APIs and open - source projects were found in GitHub, to enhance the user experience with the application. Please refer to this link to see the stack used.

Thoroughly analyzed data from here and found the mean, median, variance, and standard deviation using Python. In addition to that, I made predictions, built models, and tested them for the dataset at hand. So started analyzing the data by checking the data type of each input variable is right, and if not, correct them. Then, I checked for any missing values, meaning getting rid of the empty spaces (the NaN values). After cleaning the data, I made graphs to gain more insight. Finally, I used the one-hot-encoding to improve the prediction and classification of my analysis, split and tested the data to get more understanding and started training them for the models. These are the models used in this project: Logistic project Regression, Support Vector Machine, K Nearest Neighbors, Decision Trees, Random Forests. And finally, choose the best model by analyzing the accuracy, precision, recall, and F-1 score. However, the goal of this project was to find out which types of customers are less likely to end the service.