#!/usr/bin/env python
# coding: utf-8

# # Change this to the title of your project

# *by Chuck Anderson, October, 2023* 
# 
# Change the above line to be your name and date.  Include names of all team members, if this is a team project.

# Please follow the structure of this example proposal.  For the proposal, change all text except the headings.
# 
# At the end is a code cell that counts words for you.
# 

# ## Introduction

# Summarize the machine learning concepts, algorithms, and data that interest you.  Describe why you are interested in these.  
# 
# Very briefy describe your planned methods.

# ## Methods

# Describe in some detail the algorithms and data you will use.  In your final report cite articles and github cites like this [Goodfellow, et al., 2016].
# 
# In your proposal, make a table here with at least 5 milestones for your project with expected dates.
# 
# REQUIRED: If this is a team project, clearly describe in detail what each team member will do.

# ## Results

# In the proposal, summarize what you expect your results to be.  
# 
# In the final report, show all results.  Intermediate results might be shown in above Methods section.  Plots, tables, whatever is needed to tell your story.

# ## Conclusions

# In your proposal, describe what you expect to learn and what you expect will be most difficult.
# 
# In your project report, describe what you learned, and what was most difficult.  Summarize any surprises you encontered.

# ### References

# * [Goodfellow, et al., 2016] Ian Goodfellow and Yoshua Bengio and Aaron Courville, [Deep Learning](http://www.deeplearningbook.org), MIT Press. 2014.

# There is no word count expectations for your proposal.
# 
# Your final report should contain 2,000 to 3,000 words, times the number of team members.  Projects with two people, for example, should contain 4,000 to 6,000 words.
# 
# Count words by running the following python code in your report directory.  Do this before you check-in this notebook so the word count appears as the output of the following code cell.

# In[1]:


import io
import nbformat
import glob
nbfile = glob.glob('Project Proposal and Report Example.ipynb')
if len(nbfile) > 1:
    print('More than one ipynb file. Using the first one.  nbfile=', nbfile)
with io.open(nbfile[0], 'r', encoding='utf-8') as f:
    nb = nbformat.read(f, nbformat.NO_CONVERT)
word_count = 0
for cell in nb.cells:
    if cell.cell_type == "markdown":
        word_count += len(cell['source'].replace('#', '').lstrip().split(' '))
print('Word count for file', nbfile[0], 'is', word_count)


# In[ ]: