correct readme.md

docs/Docker reference/Docker.md

@@ -46,64 +46,6 @@ If you don't want to download the dataset each time you run your script, you can
 docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
 ```
 
-2. Set correct path to the dataset.  
-```text
-openml_tensorflow.config.dir = '/app/dataset/Images'
-``` 
-
-## Environment Variable 
-
-You can configure the cache directory to control where 'OpenML' datasets are downloaded and cached.
-
-```
-cache_dir = "/app/.openml"
-openml.config.set_root_cache_directory(cache_dir)
-```# OpenML-Tensorflow container
-
-The docker container has the latest version of OpenML-Tensorflow downloaded and pre-installed. It can be used to run TensorFlow Deep Learning analysis on OpenML datasets. 
-This document contains information about:
-
-[Usage](#usage): how to use the image\
-[Using Locally Stored Datasets](#using-locally-stored-datasets-optional): mounting datasets from the local cache\
-[Environment Variables](#environment-variable): setting the cache directory path\
-
-## Usage
-
-These are the steps to use the image:
-
-1. Pull the docker image 
-```
-docker pull taniyadas/openml-tensorflow:latest
-```
-2. If you want to run a local script, it needs to be mounted first. Mount it into the 'app' folder:
-```text
-docker run -it -v PATH/TO/CODE_FOLDER:/app taniyadas/openml-tensorflow /bin/bash
-```
-You can also mount multiple directories into the container (such as your code file directory and dataset directory ) using:
-```text
-docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
-```
-3. Please make sure to give the correct path to the dataset. For example, 
-```text
-openml_tensorflow.config.dir = 'dataset/Images'
-```
-4. Run your code scripts using, for example:
-```text
- python docs/Examples/tf_image_classification.py
-```
-
-## Using Locally Stored Datasets 
-
-If you don't want to download the dataset each time you run your script, you can mount your dataset saved in your local cache directory to the container. 
-
-### Example Usage
-
-1. Mount the dataset to the 'app/dataset' folder
-
-```
-docker run -t -i -v PATH/TO/CODE_FOLDER:/app -v PATH/TO/DATASET_FOLDER:/app/dataset taniyadas/openml-tensorflow /bin/bash
-```
-
 2. Set correct path to the dataset.  
 
 ```