Install Jupyter and required libs and datasets

python-ml-notebook-windows

1. Download 3.7

https://www.python.org/ftp/python/3.7.0/python-3.7.0-amd64.exe

Assuming that you will install Python 3.7 into C:/Python37 and allow Python installer to add python.exe into Windows's PATH environment variable.

2. Upgrade Python's pip 

python -m pip install --upgrade pip

3. Create a text file install.txt with the following content

numpy
pandas
spacy
sklearn
keras
xlsxwriter
nltk
networkx
jupyter
easydict
xlrd

4. Save it into C:/Python37

5. Install libraries that are mentioned in install.txt

Change the current directory to Python 3.7 installation directory

cd C:\Python37

then 

pip install -r install.txt

It should take a while, depending on your Internet connection. Normally, it takes 5-10 minutes

6. Install required NPL datasets

python -m spacy download en_core_web_lg

then 

python -m spacy download en_core_web_sm

It will download about 1Gb+ data. It may take 10 minutes to several hours, depending on your Internet connection.

7. Download your ML code from Github/Bitbucket and extract it into your chosen directory: e.x C:/AI-for-ticket-data-master

Change your current directory to the above directory

cd C:/AI-for-ticket-data-master

then 

jupyter notebook

It will open up a new browser window. In the address field, you will find http://localhost:8888/tree 

Now you should see all the file in the current directory as if you were using a Windows file manager. Any file that ends up with .ipynb is called a notebook, which contains ML Python code that you can run step by step.

Document can be found here https://jupyter-notebook.readthedocs.io/en/stable/