Kojak

6 weeks project (including Fletcher):

Goal : Beauty product recommendation.

   1) Get Amazon Data and Nordstrom Data
   
   2) Create a better sorting algorithm 
     (based on number of stars : Laplace transformation, and weight 1-start review heavier)
   
   3) Natural Language processing : TF-IDF, Document Summarization, Sentiment Analysis Graph (vs Star-Graph)
          * Build product-user-profile : skin type and sensitivity
   
   
   4) Build an application where the user can type in specify requirement for the product. 
   		Based on text comparison, return a maximum of 3 products as recommendations.

UP AND RUNNING : Beauty3.ninja (currently under maintenance)

Website name explained:

beauty3 : We only recommend 3 beauty products at a times (yay, no overwhelming amounts of products)

.ninja : Because just as ninja, we are highly skilled and precise. (secretly, as always come with "ninja", is because it's awesome :D)

Name		Name	Last commit message	Last commit date
Latest commit History 57 Commits
.ipynb_checkpoints		.ipynb_checkpoints
.DS_Store		.DS_Store
Built_User_Profile.ipynb		Built_User_Profile.ipynb
Built_User_Profile1.ipynb		Built_User_Profile1.ipynb
Data Scraping.ipynb		Data Scraping.ipynb
Kojak_Fletcher.ipynb		Kojak_Fletcher.ipynb
README.md		README.md
add_price.py		add_price.py
amazon_data_sort.py		amazon_data_sort.py
awake_beauty.html		awake_beauty.html
backup		backup
distance_measure.py		distance_measure.py
doc_summarization.py		doc_summarization.py
item_sentiment.py		item_sentiment.py
kojak_app.py		kojak_app.py
product_user_profile.py		product_user_profile.py
recommend_15.py		recommend_15.py
reviews.py		reviews.py

fototo/Beauty-Product-Recommendation-Engine

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