<jupyter_start><jupyter_text>Setting up local environment  for machine learningFocused on using Keras with Tensorflow and PyTorch Assuming Windows InstallationHigh Level Steps:1. Install Python version 3.6.* (latest is 3.6.8)2. Get get-pip.py ( You may need to setup proxy if behind firewall)3. Using pip, install the minimum python modules4. Install Pytorch manually5. Optionally install plaidml keras backend  Install Python 3.6.8 on Windowsdownload the 64bit version fromhttps://www.python.org/downloads/Install to non-standard path ( Not under Program... folder ) and include in the path![Install](images/python_install.jpg)Once installed, rebootThen open a command window and type:```python --version```You should see somthing like:```Python 3.6.8```  Down the latest get-pip.pyUsing a web browser, navigate to:https://bootstrap.pypa.io/get-pip.pyAnd save the content to to a file: `get-pip.py`  setup proxy before downloading pipopen command window and execute:```dosset http_proxy=http://proxy.companyname.com:portset https_proxy=http(s)://same as aboveorset https_proxy=http(s)://'id:pw'@proxy.companyname.com:port``` Execute below to download pip```python get-pip.py```  download python modules using pip -r requirement.txtcreate a file: `requirement.txt` with the following content:```absl-py >= 0.7.0astor >= 0.6.0gast >= 0.2.0google_pasta >= 0.1.2keras_applications >= 1.0.6keras_preprocessing >= 1.0.5numpy >= 1.14.5, < 2.0six >= 1.10.0protobuf >= 3.6.1tensorboard >= 1.13.0, < 1.14.0tensorflow_estimator >= 1.13.0rc0, < 1.14.0rc0termcolor >= 1.1.0urllib3pyYAMLscipymatplotlibpillowsimpynosepydotpandasnltkspacyscikit-learntensorflow==1.13.1jupyternotebookkeras```Execute below to start auto downloading the modules:```python -m pip -r requirements.txt```  Manually download and install PyTorchhttps://pytorch.org/get-started/locally/![PyTorch](images/pytorch.jpg)Click the appropriate boxes and execute the command that appears  Verify everything with Jupyter NotebookExecute below to bring up jupyter notebook```jupyter notebook```And run the below<jupyter_code>import torch
import tensorflow as tf
from tensorflow import keras

print('torch version:', torch.__version__)
print('tensorflow version:', tf.__version__)
print('keras version:', keras.__version__)<jupyter_output>torch version: 1.0.1
tensorflow version: 1.13.1
keras version: 2.2.4-tf
{'fraction_non_alphanumeric': 0.11224057602710716, 'fraction_numerical': 0.03600169419737399, 'mean_word_length': 5.653521126760563, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 16, 'https://': 3, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 7, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '627149', 'license': 'Apache-2.0', 'n_tokens_mistral': 794, 'n_tokens_neox': 739, 'n_words': 219, 'path': 'env_setup.ipynb', 'repo_name': 'sspak9/jup', 'size': '2361'}