Kelly Betting & Football Predictions

This is a Data Science project in which we are going to create a machine learning model to make prediction of a football match and betting prediction.
Frameworks and Libraries
- Sklearn: Simple and efficient tools for predictive data analysis
- Matplotlib : Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
- Numpy: Caffe-based Single Shot-Multibox Detector (SSD) model used to detect faces
- Pandas: pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- Seaborn: pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- Pickle: The Pickle module implements binary protocols for serializing and de-serializing a Python object structure.
📈 Visualising data
Data Preprocessing
Data pre-processing is an important step for the creation of a machine learning model. Initially, data may not be clean or in the required format for the model which can cause isleading outcomes. In pre-processing of data, we transform data into our required format. It is used to deal with noises, duplicates, and missing values of the dataset. Data pre- rocessing has the activities like importing datasets, splitting datasets, attribute scaling, etc. Preprocessing of data is required for improving the accuracy of the model.
Prerequisites
All the dependencies and required libraries are included in the file <code>
requirements.txt </code>
See here
Installation
The Code is written in Python 3.7. If you don’t have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after cloning the repository:
- Clone the repo
git clone https://github.com/Chaganti-Reddy/Kelly-Betting.git
- Change your directory to the cloned repo
cd Kelly-Betting
- Now, run the following command in your Terminal/Command Prompt to install the libraries required
python3 -m virtualenv kelly_b
source kelly_b/bin/activate
pip3 install -r requirements.txt
How to Run
- Open terminal. Go into the cloned project directory and type the following command:
cd Deploy
python3 main.py