Data Augmentation in NLP

Augment your Dataset and Outperform

Created by : Rated :4.2 8704 views

Last Updated: 2022-07-25 09:07:30 English Course Type: Self Learning

Data Augmentation using Word Embeddings
Data Augmentation using Word Embeddings - Implementation
Data Augmentation using BERT
Data Augmentation using BERT - Implementation
Data Augmentation using Back Translation
Data Augmentation using Back Translation - Implementation
Data Augmentation using T5
Data Augmentation using T5 - Implementation
Improving Quality of Augmented Data using Similarity Filter
Ensemble Approach for Data Augmentation
Comparison of Data Augmentation Techniques

You might have optimal machine learning algorithm to solve your problem. But once you apply it in real world soon you will realize that you need to train it on more data. Due to lack of large dataset you will try to further optimize the algorithm, tune hyper-parameters or look for some low tech approach. Most state of the art machine learning models are trained on large datasets. Real world performance of machine learning solutions drastically improves with more data.

Through this course you will learn multiple techniques for augmenting text data. These techniques can be used to generate data for any NLP task. This augmented dataset can help you to bridge the gap and quickly improve accuracy of your machine learning solutions.

Basic knowledge of machine learning and NLP is good to have

Anyone interested in machine learning and NLP

Section 1 : Introduction 1 Lectures 00:00:00
Lecture 1 :
Introduction Preview
Section 2 : Word Embeddings 2 Lectures 00:03:30
Lecture 1 :
Data Augmentation using Word Embeddings
Lecture 2 :
Implementation
Section 3 : BERT 2 Lectures 00:00:00
Lecture 1 :
Data Augmentation using BERT
Lecture 2 :
Implementation
Section 4 : Back Translation 2 Lectures 00:00:00
Lecture 1 :
Data Augmentation using Back Translation
Lecture 2 :
Implementation
Section 5 : T5 2 Lectures 00:00:00
Lecture 1 :
Data Augmentation using T5
Lecture 2 :
Implementation
Section 6 : Ensemble Approach 2 Lectures 00:04:30
Lecture 1 :
Similarity Filter
Lecture 2 :
Ensemble Approach
Section 7 : Comparison 1 Lectures 00:03:40
Lecture 1 :
Comparison

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Prathamesh Dahale,

8704 Course Views

1 Courses

Hey, I am Prathamesh! Over last 5 years I have worked on several technologies. To quickly ramp up on new technologies, all you need is structured and to the point learning content. But its hard to find learning material on latest technologies that can be completed over the weekend and quickly applied in real project. This motivated me to start creating short and easy to understand courses on cutting edge technologies.