from kaggle natural language processing
-
Updated
Jun 30, 2017 - R
Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
from kaggle natural language processing
To find the accurate review and sentiment about the product and tag the opinion as positive, negative or neutral.
Applying unsupervised learning using K-means clustering.
Academic project for Advances in Data Science and Architecture course
Predicting NEXT word - Data Science Capstone Project by Johns Hopkins University on Coursera
As a customer or a potential investor who lists properties on Airbnb, one would always be interested in determining the quality of the listing. The rating score is one of the indicators which every stakeholder looks forward to, in order to gauge this metric. It is often observed that this is not an accurate indicator.
In this project, we implemented the detection algorithm (D-3 in the folder: ''doc/paper'') and correction algorithm (C-3 in the folder: ''doc/paper'') for post-processing of OCR technique.
Analyzing ratings and reviews for restaurants across 31 European cities
Sentiment Analysis on Demonetization tweets
A repo for analysing sentiments in WhatsApp Chat
In this project, I analyzed the NLP data of all the pitches in 'Sharktank' and generated a model to predict the significance of keywords in getting a deal using Random Forest & Decision trees.
Natural Language Processing to predict future words in text prediction app
Data: Goodreads.com
Computational literature review of water resources research in Latin America and the Caribbean.
textRec utlizes Latent Dirichlet Allocation and Jensen-Shannon-Divergence on the discrete probability distributions over LDA topics per document, in order to recommend unique and novel documents to specific users.
Research project to measure the firm Expected Investment Growth (EIG) based on a combination of machine learning tools and text regression.
Homework assignments from the course, Big Data. Topics covered include: data warehousing, linear regression, NLP, KMeans, TF-IDF, PCA, decision trees, data cleaning, and recommendation systems - UBCF and IBCF. The assingments were completed with the following tools: R, RStudio, DataGrip, MySQL, and R libraries such as ggplot2, recommenderlab, qu…
Created by Alan Turing