Deep Learning NLP: Build and Deploy a BERT COVID Q&A System

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Deep Learning NLP: Build and Deploy a BERT COVID Q&A System
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 3.04 GB | Duration: 4h 45m



What you'll learn
Develop a BERT Q&A system that provides real-time answers from over 200,000 COVID research papers
Accessing and pre-processing the COVID dataset
Perform Exploratory data analysis and Topic modelling on the COVID dataset
Create an indexed database of COVID research text in Elasticsearch
Build an algorithm that retrieves and ranks candidate documents from Elasticsearch
Develop the BERT Q&A Engine
Build End point creation with fast API
Building a simple UI with Streamlit
Dockerize and deploy models
Working with google colab and Visual studio code

Description
If you are interested to learn about NLP and looking to work on one of the biggest real world NLP projects, then this course is for you.
This course has been designed by professional data scientists and our sole passion is to enable our students to develop and deploy state of the art Deep Learning NLP models.
Our students will learn new skills at every step and section of our course and will be able to develop and deploy an NLP Q&A system that can retrieve answers from a database consisting of over 250,000 COVID research papers.
In this course, we code everything and hence the program is very much project based. The entire program is comprehensive in a way that you can easily extend the algorithms, tools to deploy a NLP Question Answering system on another topic of interest.
We have worked hard to organize the structure of this course in a way that you could apply it to any NLP project in your work or studies. It is structured in the following way
· Section 1: All instruments you need to complete the course
· Section 2: Accessing and saving COVID dataset
· Section 3: Data pre-processing
· Section 4: Exploratory data analysis
· Section 5: Creating Knowledge base in Elasticsearch
· Section 6: Create BERT QA Engine
· Section 7 : Frontend with streamlit
· Section 8 : Dockerizing and deploying
All the sections include bonus/resource materials to deep dive into the concepts. You can evaluate your understanding by participating in funny yet exciting quizzes.
Waiting to welcome you to be part of this journey!!
Who this course is for
Anyone interested in Deep Learning and Natural Language Processing
Any students in college interested in a career in Data Science
Anyone with basic to intermediate level knowledge of BERT and Natural language processing models
Any business owners who are interested in building real-life NLP Question and Answering systems
Finally, this course for anyone who enjoys learning and loves a challenge?

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