Aniket_Patil = {'I_am' : ['Data science professional of 3 years', 'Learner of a lifetime'], 'Education' : ['MS in Business Analytics', 'BE in Computer Engineering'], 'Tech_stack' : ['Python', 'R', 'SQL', 'AWS', 'Azure', 'Power BI', 'Tableau'], 'Certifications' : ['Azure Data Analyst Associate','Azure Data Fundamentals'], 'Skills' : ['Machine Learning', 'Optimization', 'Visualization', 'Data Transformation', 'A/B Testing'], 'Passions' : ['Formula One', 'Fitness']}
aniketcomps / clustering-food-items Goto Github PK
View Code? Open in Web Editor NEWClustered a database of food items into appropriate segments (veg, non-veg, drinks, etc) using an unsupervised approach. I have used Word2Vec, SpaCy, GloVe and cosine similarity matrices. Example input: (.csv file) Item_name: Paneer Wrap, Whiskey, Chicken Tikka Example output: (.csv file) Item_name & label: Paneer Wrap veg, Whiskey alcohol, Chicken Tikka non-veg The actual database contains around 30000 rows.