IMDb-Scraping is for retrieving user-generated movie text reviews as well as relevant movie characteristics from imdb.com.
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Updated
Sep 6, 2020 - Python
IMDb-Scraping is for retrieving user-generated movie text reviews as well as relevant movie characteristics from imdb.com.
This is a simple graphical representation of Zipf's Law using term frequencies, calculated for three different text data.
The aim of this work is to predict number of instagram likes. The text vectorization is done using TF-IDF Vectorizer.
Rank 3/85 MachineHack
Rank 16/98 MachineHack
This project is built using React. The data is fetched online in a text form and then split them into chunks of arrays depending on the Table of Contents. For example, main headings were put in one array and subheading in another array and the content in different array. In the end data is displayed on the screen.
Just a bunch of experiments with embedded graph databases
28237-Intent-type-single-sentence-annotation-data
A tutorial on using regular expressions in R
8178-Chinese-Social-Comments-Events-Annotation-Data
The objective of the project is to predict whether a particular tweet, of which the text (occasionally the keyword and the location as well) is provided, indicates a real disaster or not. We use various NLP techniques and classification models for this purpose and objectively compare these models by means of appropriate evaluation metric.
Extract technical skills from data of skills
Scrape EDGAR filings from https://www.sec.gov/
An algorithm to generate the word cloud for time-varying dynamical text data in order to minimize the relative movement of the word over time.
13-Modules-Entity-Name-Single-sentence-Annotation-Data
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