[Chore]:

- Update ReadME file

README.md

@@ -1,39 +1,19 @@
-# Data Science Repo Template
+# Optimization And Image Classifier
+
+## Milestone I
+### Description
+You will compare between the performance of the following optimization algorithms:
+ - Stochastic gradient descent
+ - Gradient descent with momentum
+ - Gradient descent with adaptive learning rate. You need to implement a 
+linear search method to tune the learning rate in each iteration.
+- Adagrad
+- Adam
+
+### Approach
+- Build each optimizer to by easily to integrate with tensorflow models that build on top of `tf.keras.models` and utilize the built-in loss functions that was inherited from `tf.keras.losses` base classes
+- Build `SGD trainer` that could utilize any of the implemented `Optimizers`  
+- all implemented Optimizer are inheriting from the base class `Optimizer` that exists on `/optimization/optimizers.py`
+- Build Unit tests (using **Pytest**) for each part of the code to ensure the correctness and to be easily used independently without any issues
 
-## Project structure
 
-```bash
-.
-├── data
-│   ├── processed
-│   │   └── v1
-│   ├── raw
-│   │   └── v1
-│   ├── scripts
-│   │   ├── extract.py
-│   │   ├── transform.py
-│   │   └── load.py
-│   └── main.py
-├── deploy
-│   ├── scripts
-│   └── tests
-├── develop
-│   ├── artifacts
-│   ├── eda
-│   ├── notebooks
-│   ├── scripts
-│   │   ├── eda.py
-│   │   └── load.py
-│   └── main.py
-├── label
-├── train
-├── visualise
-├── .flake8
-├── .gitattributes
-├── .gitignore
-├── .pre-commit-config.yaml
-├── Makefile
-├── poetry.toml
-├── pyproject.toml
-└── README.md
-```