A Data Analysis Project on the Tunisian and Egyptian Springs
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Oct 21, 2018 - HTML
A Data Analysis Project on the Tunisian and Egyptian Springs
A Pytorch Implementation of LDA2VEC : "Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec"
Code to train a LSI model using Pubmed OA medical documents and to use pre-trained Pubmed models on your own corpus for document similarity.
Scrape Reviews about Amazon Shopping App on Google CH Play and Perform Topic Modelling by LDA (Latent Dirichlet Allocation) using Python
Identification of papers/websites/documents with context related to a given context or abstract | Runners-up at Megathon 2k19 for Qualcomm
I don't feel like reading this research paper that my professor has us doing so I made this summarizer using Latent Dirichlet Allocation
In this module you will learn how to analyze topic modeling output from Amazon Comprehend, then perform topic modeling on two documents with a known topic structure.
This module looks at how use Amazon Connect, Lex, and Lambda to interact with a chatbot using voice. You will create a personal call center using Amazon Connect and you will learn how to connect the call center to your Lex chatbot
This module teaches you how to design a chatbot using Amazon Lex by following the best design practices for conversational AI. You will start by learning the basics of chatbots. Then, you will use Amazon Lex to create a custom chatbot that gets the latest stock market quotes by recognizing the intent in text
This chapter covers the Amazon Rekognition service for analyzing the content of the images using various techniques. You will learn how to analyze faces and recognize celebrities in images. You will also be able to compare faces in different images to see how closely they match with each other.
The project provides insights for business owners to improve their businesses and recommendations for users to improve their experience with the application
A Blog application with features such as generating relevant tags and keywords from blogs in order to generate recommendations for users. Application made using Django. Joint Project by Swebert Correa and Jinit Sanghvi.
Analysis of social media conversations surrounding COVID-19 in Singapore
Analysing the top news headlines topics in Australia.
Materials and approach utilized for competing in 10-day long hackathon hosted by Analytics Vidhya. Given a set of research articles, it's category has to be classified.
Topic Modelling to segregate news report data to different topics using Gensim, NLTK, Spacy.
This app has been created by a group of students as part of a course in the Data Science Master’s Program at the University of Helsinki. The app was created for, and in collaboration with, the Research Unit for the Study of Variation, Contacts, and Change in English (VARIENG). It allows for the exploration of a corpus of historical letters.
Implementation and helper scripts for the BART-TL model - https://www.aclweb.org/anthology/2021.eacl-main.121/
Small tutorial on how you can use BERT for Topic Modeling
Add a description, image, and links to the topic-modelling topic page so that developers can more easily learn about it.
To associate your repository with the topic-modelling topic, visit your repo's landing page and select "manage topics."