added basic desc in readme

README.md

@@ -1,19 +1,44 @@
-# partiqlegan
+# PartiqleDTR
 
+Repository of the Partiqle Decay Tree Reconstruction (DTR) project.
+The PartiqleDTR project attempts to tackle the problem of particle decay tree reconstruction using hybrid quantum-classical machine learning approaches.
 
-decayfile -> decaytree -> decayevents
-
-masses -> decaytopologies (containing decaytrees) -> decayevents
-
-
-## Installation
+## :rocket:  Setup and Run
 
 1. Clone the repository
-2. Create a venv
-3. Install the requirements using
-```bash
-pip compile 
-```
+2. Install dependencies
+   - **Option A:** Poetry installed on your system
+   ```
+   poetry install
+   ```
+   - **Option B:** Create a venv, and install dependencies from ```pyproject.toml``` manually
+3. Create a dataset and run training using the existing parameters:
+   ```
+   kedro run
+   ```
+
+## :wrench: Configuration
+
+*The command prefix ```poetry run``` can be omitted if you're using an already activated venv*
+
+- Pipeline Configuration:
+  - Open visualization: ```poetry run kedro viz```
+  1. Data Generation:
+     - Builds decay tree
+     - Generates decay events
+  2. Data Processing
+     - Preprocessing events
+     - Generating datasets
+  3. Data Science
+     - Model creation
+     - Training
+- Parameters can be adjusted in the following locations:
+  - ```conf/base/parameters/data_generation.yml```
+  - ```conf/base/parameters/data_processing.yml```
+  - ```conf/base/parameters/data_science.yml```
+- Runs are being recorded using MLFlow
+  - Open dashboard: ```poetry run mlflow ui```
+
 ## Notes
 
 torch_scatter needs gcc-c++ and python3-devel packages to build successfully.