Rajshree Vatsa's starred repositories
Intelligent-Travel-Recommendation-System
The project provides a Tailor-made travel itinerary for users using their travel details like destination, budget, start and end dates of travel and their preferences of attraction categories, hotel amenities and cuisine type. Our project significantly reduces the time spent on planning for a satisfactory vacation.
Chat-Bot-with-Sentiment-Analysis
A Chat-Bot integrated with Request-Response Sentiment Analysis for results worked up on Python.
chatbot-sentiment-analyzer
A sentence by sentence sentiment analyzer ready to use by chatbots
developer-portfolios
A list of developer portfolios for your inspiration
DAA-lab-files
This repository contains C programs done in DAA lab in 4th semeter , KIIt University
computer-networks-lab
assignments from the computer network labs. Socket Programming
Computer-Network-Lab---KIIT-2020-2021-
Computer Networking Lab Program.
6thSemLabPrograms
CNS, CN and WT lab programs
sentence-transformers-example
HuggingFace's Transformer models for sentence / text embedding generation.
inf368-exercise-3-coordle
INF368 Spring 2020 Exercise 3 - Coordle pip package
stackoverflow-semantic-search
Word2Vec encodings based search engine for Stackoverflow questions
mood-based-food-recommender
It recommends restaurants in New Delhi based on User Moods and Other Filters.
travel-recommendation-engine
A Travel Recomendation Engine: based off of user's input (keywords and maximum price per pay), this engine recommends cities to visit. It uses NLP approach.
Grocery-Recommendation-System-NTI-Project-
a Recommendation Engine using association rule with"Apriori" Algorithm we using the data set "order_products__prior.csv" with 42 million record to build our back end recommendation engine, we end up with an android mobile application as a front end, also we used PythonAnyWhere.com to build our API using FLASK.
Data-Science-Machine-Learning-Zinmat-Insurance-Recommendation
Zinmat Insuarance Recommendation Engine is trying to predict which insurance product an existing customer will want next
Spotify-Recommendation-Engine
Music Recommender System
recommendation-engine
Microsoft engage'2022 project using recommendation algorithms to recommend books and movies. Based on collaborative and content filtering methods.
music_recommendation_system
Music Recommendation System https://youtu.be/4GWFkkR7mFM
hybrid-recommender
Hybrid recommendation engine using deep learning that incorporates user and item features, including images and text.
Linedin-User-profile-Hybrid-Recommendation
Hybrid recommedation for talents
Hybrid-recommendation-system-web-application
Regression-based Movie Recommender system that's a hybrid of content-based and collaborative filtering Recommender system Simply rate some movies and get immediate recommendations tailored for you
Netflix_Movie_Recommendation_BigData
We used deep learning models on SparkML to create a hybrid recommender system that leverages both content and collaborative data.
hybrid-recommender-system
uses collaborative and content based filtering techniques
RecommenderSystem
This repository consists code to build a recommender system on the netflix movie recommendation data.
recommendation-engine
Devise a Movie Recommendation System based Netflix and IMDB dataset using collaborative filtering and cosine similarity. Produce a user interface to suggest content based on genre & time using Dash (Python)
fk-visual-search
Flipkart's visual search and recommendation system
Deep-Learning-Model-for-Hybrid-Recommendation-Engine
A Hybrid recommendation engine built on deep learning architecture, which has the potential to combine content-based and collaborative filtering recommendation mechanisms using a deep learning supervisor
Movie-Recommendation-Chatbot
Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM Watson was used to link the Python code for Natural Language Processing with the front end hosted on Slack API. Libraries like nltk, sklearn, pandas and nlp were used to perform Natural Language Processing and cater to user queries and responses.