Question Answering | NLP | QA | Tranformer | Natural Language Processing | Python | Theory | Code
===== Likes: 38 👍: Dislikes: 0 👎: 100.0% : Updated on 01-21-2023 11:57:17 EST =====
Question & Answering! Looking to develop a model that can provide answers to any question you have? Well, in this video, I cover the high level overview on the architecture of QA Models (based on BERT). I also go into depth on what QA Modeling is, how it can be applied, and how it is used in the real world. Lastly, I cover the pretraining and fine-tuning phases of the QA Modeling process.
Feel free to support me! Do know that just viewing my content is plenty of support! 😍
☕Consider supporting me! https://ko-fi.com/spencerpao ☕
Watch Next?
BERT → • Understanding and Applying BERT | Bidirect...
Transformers → • Transformers EXPLAINED! Neural Networks | ...
Resources
Huggingface: https://huggingface.co/deepset/robert...
🔗 My Links 🔗
Github: https://github.com/SpencerPao/spencer...
My Website: https://spencerpao.github.io/
Github Repository for Notebooks! https://github.com/SpencerPao/Natural...
📓 Requirements 🧐
Understanding of Python
Google Account
⌛ Timeline ⌛
0:00 - Categories of Question & Answering
3:20 - Additional Resources for Question & Answering
4:05 - Architecture and Backend of RoBERTa QA
5:12 - Implementation of Extractive QA (RoBERTa)
6:00 - Transfer Learning (Out of the Box Predictions)
8:45 - RoBERTa Architecture & Fine-Tuning QA Model via CLI
10:00 - Fine-Tuning QA Model with Libraries
13:15 - Pre-Training QA Model
🏷️Tags🏷️:
Python,Natural Language Processing, BERT, Question and Answering, QA, Question, Answering, Tutorial, Machine Learning, Huggingface, Google, Colab, Google Colab, Chatbot, Encoder, Decoder, Neural, Network, Neural network, theory, explained, Implementation, code, how to, deep, learning, deep learning, tasks, QA, Q&A, Extractive, Abstractive, Extractive QA, Abstractive QA,
🔔Current Subs🔔:
3,220
On this page of the site you can watch the video online Question Answering | NLP | QA | Tranformer | Natural Language Processing | Python | Theory | Code with a duration of hours minute second in good quality, which was uploaded by the user Spencer Pao 24 July 2022, share the link with friends and acquaintances, this video has already been watched 25,725 times on youtube and it was liked by 487 viewers. Enjoy your viewing!
