aniketcomps,Aniket Patil,github

Hi there 👋

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']}

Aniket Patil's Projects

bert-topic-modeling

Topic Modeling on WallStreetBets subreddit and recommending stocks based on sentiment analysis

brand-association-analysis

Identifying brand association from social media conversations

classify-toxic-comments

My attempt for Toxic Comments Classification challenge on Kaggle

Clustered 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.

crowdsourced-beer-recommender-system

Recommending beers to users based on their beer attributes preference

data-analysis-and-ml

Notebooks from my Summer Industrial Training and Internship that implement various Machine Learning algorithms

social-media-influencer-analysis

Identifying Twitter influencers of Austin city using Network Analytics

speech-emotion-recognition

Librosa library is used to train a Neural Network MLP Classifier on audio clips with different emotions. The model can determine the emotion of the speech, for eg. sad, happy, calm, normal, etc