Cod: https://nbviewer.org/github/Bryancocola/Profolio/blob/main/Titanic .ipynb

In this project, I aim to demonstrate my ability to effectively clean and process data for a machine learning model. The Kaggle Titanic Dataset serves as the primary focus of this project, which is a collection of information regarding each passenger that can be analyzed to predict their likelihood of survival during the disaster. The dataset comprises of various attributes such as the passenger's age, gender, class, fare, and embarked port. To ensure the accuracy of the model, various data preprocessing techniques such as missing value imputation, feature scaling, and encoding will be implemented. Additionally, exploratory data analysis will also be conducted on the dataset to gain a deeper understanding of the dataset and its underlying patterns. Through the completion of this project, I am confident in my ability to handle complex data manipulation tasks and deliver accurate results that can be utilized in real-world scenarios.

This project is particularly exciting for me as it enables me to showcase my proficiency in Python programming and data science concepts. I plan to use several Python libraries such as pandas, numpy, and scikit-learn to manipulate and analyze the dataset. The project will involve various stages such as data collection, data cleaning, exploratory data analysis, feature engineering, model selection, and evaluation.

Overall, I am excited to undertake this project and demonstrate my skills in data science. I believe that this project will not only help me improve my technical skills but also provide me with valuable experience that I can leverage in future projects.