Update README.md

* [joblib](https://pypi.python.org/pypi/joblib)

* [sklearn](https://github.com/scikit-learn/scikit-learn.git)

* [numpy](https://store.continuum.io/cshop/anaconda/)

* [theano](http://deeplearning.net/software/theano/)

* [keras](http://keras.io)

* [six](https://pypi.python.org/pypi/six)

* [dill](https://pypi.python.org/pypi/dill)

Linux (64-bit) Installation 

---------------------------

```deepchem``` currently requires Python 2.7, and is not supported on any platforms except 64 bit linux. Please make sure you follow the directions below precisely. While you may already have system versions of some of these packages, there is no guarantee that `deepchem` will work with alternate versions than those specified below. This is especially true for the `keras` library, where `deepchem` is known not to work with the latest default version.

```deepchem``` currently requires Python 2.7, and is not supported on any platforms except 64 bit linux. Please make sure you follow the directions below precisely. While you may already have system versions of some of these packages, there is no guarantee that `deepchem` will work with alternate versions than those specified below.

1. Anaconda 2.7

   Download the **64-bit Python 2.7** version of Anaconda for linux [here](https://www.continuum.io/downloads#_unix).  

   conda install joblib 

   ```

7. `theano`

7. `keras`

   ```bash

   conda install -c omnia theano

   pip install keras

   ```

8. `keras`

   ```bash

   conda install -c omnia keras

   ```

9. `six`

8. `six`

   ```bash

   conda install six

   ```

10. `dill`

9. `dill`

    ```bash

    conda install dill

    ```

11. `ipyparallel`

10. `ipyparallel`

    ```bash

    conda install ipyparallel

    ```

12. `mdtraj`

11. `mdtraj`

   ```bash

   conda install -c omnia mdtraj

   ```

13. `scikit-learn`

12. `scikit-learn`

    ```bash

    conda install scikit-learn 

    ```

14. `tensorflow`: Installing `tensorflow` on older versions of Linux (which

13. `tensorflow`: Installing `tensorflow` on older versions of Linux (which

    have glibc < 2.17) can be very challenging. For these older Linux versions,

    contact your local sysadmin to work out a custom installation. If your

    version of Linux is recent, then the following command will work:

    conda install -c https://conda.anaconda.org/jjhelmus tensorflow

    ```

15. `deepchem`: Clone the `deepchem` github repo:

14. `deepchem`: Clone the `deepchem` github repo:

    ```bash

    git clone https://github.com/deepchem/deepchem.git

    ```

    python setup.py install

    ```

16. To run test suite, install `nosetests`:

15. To run test suite, install `nosetests`:

    ```bash

    pip install nose 

    ```

    You might need to uninstall a system install of `nosetests` if

    there is a conflict.

17. If installation has been successful, all tests in test suite should pass:

16. If installation has been successful, all tests in test suite should pass:

    ```bash

    nosetests -v deepchem --nologcapture 

    ```

    Note that the full test-suite uses up a fair amount of memory. 

    Try running tests for one submodule at a time if memory proves an issue.