BERT Text Classification Kaggle NLP Disaster Tweets TensorFlow

In this video I will be explaining my solution to Kaggle Natural Language Processing with Disaster Tweets (Getting Started Competition). I will be using BERT(Tensorflow) in the solution
The main purpose of the competition is Twitter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they’re observing in real-time. Because of this, more agencies are interested in programmatically monitoring Twitter (i.e. disaster relief organizations and news agencies).

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The code is present here: https://github.com/rsreetech/Disaster...
Relevant Links:
Kaggle competition link:
https://www.kaggle.com/c/nlp-getting-...
Kaggle Notebook Link: https://www.kaggle.com/ritheshsreeniv...
BERT resources:
http://jalammar.github.io/illustrated...
https://jalammar.github.io/illustrate...
http://jalammar.github.io/a-visual-gu...
https://www.tensorflow.org/tutorials/...



Chapters/Timestamps :
00:00 Kaggle Natural Language Processing with Disaster Tweets – Top 14% Solution with BERT (TensorFlow) #NLProc
00:28 Natural Language Processing with Disaster Tweets
01:38 Train,Test dataset description
02:39 Solution description
03:33 BERT discussion
08:27 Dataset exploration, pre-processing TensorFlow additional packages
11:40 TensorFlow additional packages
12:19 TensorFlow dataset creation
12:42 BERT model and pre-processing pipeline selection
14:15 Classification model creation and training followed by prediction