diff --git a/README.md b/README.md
index cff3f2e5f..98ff13d04 100644
--- a/README.md
+++ b/README.md
@@ -1,10 +1,53 @@
# NBA Sports Betting Using Machine Learning 🏀
-A machine learning AI used to predict the winners and under/overs of NBA games. Takes all team data from the 2007-08 season to current season, matched with odds of those games, using a neural network to predict winning bets for today's games. Achieves ~75% accuracy on money lines and ~58% on under/overs. Outputs expected value for teams money lines to provide better insight. The fraction of your bankroll to bet based on the Kelly Criterion is also outputted. Note that a popular, less risky approach is to bet 50% of the stake recommended by the Kelly Criterion.
+A machine learning AI used to predict the winners and under/overs of NBA games.
+
+## About
+
+Takes all team data from the 2007-08 season to current season, matched with odds of those games, using a neural network to predict winning bets for today's games.
+
+ Achieves ~75% accuracy on money lines and ~58% on under/overs.
+
+## Betting Strategy
+Outputs expected value for teams money lines to provide better insight. The fraction of your bankroll to bet based on the Kelly Criterion is also outputted.
+
+ Note that a popular, less risky approach is to bet 50% of the stake recommended by the Kelly Criterion.
+
+## Installation
+*Side comment:
+Make sure you use Python 3.8. If for some reason "python3" does not work, try using "python" instead.*
+### Installing the source code
+```
+git clone https://github.com/kyleskom/NBA-Machine-Learning-Sports-Betting.git
+```
+
+### Create environment
+
+Navigate into to project and create an environment
+```
+cd NBA-Machine-Learning-Sports-Betting
+```
+```
+python3 -m venv env
+```
+### Activate environment
+On Windows:
+```
+source env\Scripts\activate.bat
+```
+On Unix/MacOS:
+```
+source env/bin/activate
+```
+
+### Install packages
+```
+python3 -m pip install -r requirements.txt
+```
## Packages Used
-Use Python 3.8. In particular the packages/libraries used are...
+In particular the packages/libraries used are...
* Tensorflow - Machine learning library
* XGBoost - Gradient boosting framework
@@ -21,42 +64,43 @@ Use Python 3.8. In particular the packages/libraries used are...
Make sure all packages above are installed.
-```bash
-$ git clone https://github.com/kyleskom/NBA-Machine-Learning-Sports-Betting.git
-$ cd NBA-Machine-Learning-Sports-Betting
-$ pip3 install -r requirements.txt
-$ python3 main.py -xgb -odds=fanduel
```
-
-Odds data will be automatically fetched from sbrodds if the -odds option is provided with a sportsbook. Options include: fanduel, draftkings, betmgm, pointsbet, caesars, wynn, bet_rivers_ny
+python3 main.py -xgb -odds=fanduel
+```
+*Note:
+Odds data will be automatically fetched from **sbrodds** if the -odds option is provided with a sportsbook. Options include: fanduel, draftkings, betmgm, pointsbet, caesars, wynn, bet_rivers_ny*
If `-odds` is not given, enter the under/over and odds for today's games manually after starting the script.
-Optionally, you can add '-kc' as a command line argument to see the recommended fraction of your bankroll to wager based on the model's edge
-
-## Flask Web App
-
-
-This repo also includes a small Flask application to help view the data from this tool in the browser. To run it:
-```
-cd Flask
-flask --debug run
-```
+Optionally, you can add `-kc` as a command line argument to see the recommended fraction of your bankroll to wager based on the model's edge
-## Getting new data and training models
+## How to get new Data and Train Models
+### Create dataset with the latest data for 2022-23 season
```
-# Create dataset with the latest data for 2022-23 season
cd src/Process-Data
python -m Get_Data
python -m Get_Odds_Data
python -m Create_Games
-# Train models
+```
+### Train models
+```
cd ../Train-Models
python -m XGBoost_Model_ML
python -m XGBoost_Model_UO
```
+## Flask Web App
+
+
+This repo also includes a small Flask application to help view the data from this tool in the browser. To run it:
+```
+cd Flask
+flask --debug run
+```
## Contributing
-All contributions welcomed and encouraged.
+All contributions welcomed and encouraged.
+
+Please abide by the Open Source Contributing Guidelines:
+https://opensource.guide/how-to-contribute/