Escuela Colombiana de Ingeniería

Final Project

1. Data Source Selection

   Select one dataset from the above open data sources or any other relevant data source.

   Considerations: The dataset should be rich enough to allow multiple analyses and should be relevant to the student’s interests or our course objectives.

2. Loading the dataset into a SQL

   Load the data set into a relational table designed in SQL database. The Professor must providethe information on a connection.

   Considerations: You can use the MySQL account provided by the professor, which is freely accessibleand will always be available while the course ends.

3. Data Preparation

   Load, clean, and preprocess the selected dataset using programming-based tools and libraries.

   Considerations: Ensure the data is ready for analysis, handle missing values, encode categorical variables, and normalize or standardize numerical variables as necessary.

4. Exploratory Data Analysis (EDA)

   Perform an initial dataset analysis using visualization techniques and statistical methods to gain insights and identify patterns, trends, and potential relationships between variables.

   Deliverable: An EDA report containing visualizations and observations about the dataset.

5. Descriptive Analysis

   Calculate summary statistics for the dataset, such as means, medians, standard deviations, quartiles, and correlations, to provide a quantitative data description.

   Deliverable: A report describing the key statistics of the dataset and their implications.

6. Inferential Analysis or Predictive Modeling

   Use inferential statistics or machine learning algorithms to make predictions or draw conclusions based on the data.

   Deliverable: A report detailing the model selection, evaluation, and interpretation of the results, along with any actionable insights or recommendations

Prerequisites

• Python
• Jupyter Notebook
• Git

Installing

To download this project, you must run the following command down below.

git clone https://github.com/JuanPablo70/PGAD-NBA-Prediction-Project.git

Open Jupyter Notebook on your computer and open the PGAD_Project.ipynb file.

Running the notebook

Once you have opened the PGAD_Project.ipynb file, run each cell with shift + Enter or go to the Cell tab and click on Run All and see the results.

Authors

Juan Pablo Sánchez Bermúdez - JuanPablo70

Juan Camilo Bazurto Arias - juan-bazurto-eci