There are 2 repositories under ted-talks topic.
🎙️ TED Talks web scraper
Data for the DiMSUM shared task at SEMEVAL 2016
Companion code for Awe the Audience: How the Narrative Trajectories Affect Audience Perception in Public Speaking
Complete Web Scraping of TED.com for Metadata, Transcript, Audio, Video, Images using Parallel Programming
TEDxIITRAM 2022 Official Website
[PORTUGUÊS] Extração de transcrições de palestras TED Talks
Official Code Base for TEDxMITAOE
TEDxNITKSurathkal website
Android Automation Tools--Definitions from Merriam Webster and Collins using Google Assistant, A better calendar notification UI, Custom news radio and TED Video downloader with progress shown using tiny Pie chart format overlay UI. These automation tools were built using Tasker, Autoapps and IFTTT.
A character-level multi-layer LSTM to generate TED Talks
Tedx tedxmitaoe tedxalandi mitaoe tedtalk TEDxMITAOE KEDAR1023 SARVESH
Annotation of Tension Development in TED talks
This project aims to build a regression model that predicts the number of views for TED Talks videos on the TED website.
The official website of TEDx, NMIMS, Indore 🏦. Visit tedxnmimsindore.com to view the website!
These are different files I created to do different tasks when I was working on creating ASR model for mTEDx dataset.
NLP Topic Modeling Techniques (LDA, LSA & BERTopic)
Embed Ted video players in @textpattern CMS through oui_player v2+
Some exploratory data analysis of 2500+ TED talk transcripts
Preliminary EDA with Text Features
A web scraper using Beautiful Soup and Python built-in modules.
Predict which Ted-Talks belongs to which topics using Topic Modelling
It is a Capstone project. A regression model has been built using Random Forest, which can predict views for TED talk videos. The data file contains 4000+ records.
Using CNNs to perform facial expression recognition and analysing TED talks to gain insights.
There are tons of these videos across the world. They are recorded in different locations, with different topics and a variety of speakers. Tagging these videos manually to a certain category is the biggest challenge given the number of videos we have already. Let’s look at machine learning and natural language processing to solve this problem.
Just a sample practice code using Python.
automate the process of downloading TED Talks videos and playing them sentence by sentence.