samratsengupta Goto Github PK
Name: Samrat sengupta
Type: User
Company: HappiestMindsTechnologies
Bio: Lead Data Scientist and AI-ML practitioner
Location: Bangalore
Name: Samrat sengupta
Type: User
Company: HappiestMindsTechnologies
Bio: Lead Data Scientist and AI-ML practitioner
Location: Bangalore
build content based recommender from derived feature set of data of popular retail giant using idf weighted w2v based semantic similarity for text metadata and imagenet trained VGG-16 for image recommendation
Conversation based intelligent search enabling customers to look for apparels in retails store.dialogue management using Rasa core/NLU with w2v embeddings enabled search api
figure out most influencing underlying factors and design a regression model to predict car price for a chinese automobile company
identify effusion in chest Xray images using morphological transformation with Opencv for image processing and 2D-CNN for image classification.
this project does counting and classification of vehicles passing on a road using opencv based blob feature extraction to do vehicle detection and CNN based vehicle classification
This project implements a computer vision based virtual online exam proctoring software by capturing facial recognition, head pose and eye gaze through webcam using CNN based deep learning models
used Random Forest classifier to predict missing links to recommend users in a social graph generated from historical data using probabilistic grahical model
developed a 3d-cnn and conv2d(pretrained-inception)-gru to correctly recognize hand gestures by a user to control a smart TV.
Human activity recognition is the problem of classifying sequences of accelerometer data recorded by specialized harnesses or smart phones into known well-defined movements.LSTM gave best results
Carry out EDA using data visulaization techniques to figure out driving factors (or driver variables) behind loan default for a consumer finance company
to determine malwares in bytes/asm file ,carried out multivariate EDA using t-sne and implemented XgBoost Classifier on final features with best hyper parameters using Random search for classification
movie recommendation with RL
created matrix factorization (SVD) based collaborative filtering algorithm to recommend movies to netflix users based on historical preferences
Taxi demand prediction on hourly basis for Ny city.The modelling is done on moving average and fourier transform based features after applying tsne .xgboost gave best performance
paitshop optimization
Classify the given genetic variations/mutations based on evidence from text-based clinical literature.TF-IDF features along with Random Forest Classifier gave best results
To filter similar question asked in popular QA site,tried out models (Logistic regression, Linear-SVM) with TD_IDF weighted word2Vec. Hyperparameter tune XgBoost using RandomSearch to reduce the log-loss.
developed RL-based algorithm using state based DQN architecture with simulated MDP to help cab drivers effectively decide which cab-request to accept for maximum profit
developed conversational bot (chatbot)to help users discover restaurants quickly using Rasa Core and NLU framework with zomato api
Demand Forecasting for weekly storewise and productwise sales has been projected for a global retailer.An ensemble of xgboost and catboost regressor is done on lag features to arrive at final output
demand forecasting with RL
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