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Transformer models are the de–facto standard in modern NLP. They have proven themselves as the most expressive, powerful models for language by a large margin, beating all major language–based benchmarks time and time again.
In this course, we cover everything you need to get started with building cutting–edge performance NLP applications using transformer models like Google AI’s BERT, or Facebook AI’s DPR.
We cover several key NLP frameworks including:
HuggingFace’s Transformers
TensorFlow 2
PyTorch
spaCy
NLTK
Flair
And learn how to apply transformers to some of the most popular NLP use–cases:
Language classification/sentiment analysis
Named entity recognition (NER)
Question and Answering
Similarity/comparative learning
Throughout each of these use–cases we work through a variety of examples to ensure that what, how, and why transformers are so important. Alongside these sections we also work through two full–size NLP projects, one for sentiment analysis of financial Reddit data, and another covering a fully–fledged open domain question–answering application.
All of this is supported by several other sections that encourage us to learn how to better design, implement, and measure the performance of our models, such as:
History of NLP and where transformers come from
Common preprocessing techniques for NLP
The theory behind transformers
How to fine–tune transformers
Specification: Natural Language Processing: NLP With Transformers in Python
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7 reviews for Natural Language Processing: NLP With Transformers in Python
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| Price | $11.99 |
|---|---|
| Provider | |
| Duration | 11.5 hours |
| Year | 2021 |
| Level | All |
| Language | English ... |
| Certificate | Yes |
| Quizzes | No |
$11.99
Rafael Pardinas –
Really good content so far. Well structured and valuable info.
Karim Saida –
Great course
Nicholas S Sereni –
This course covered a lot of really interesting topics. However, it felt like more of an overview. Personally, I would have preferred a deeper dive into individual topics rather such a broad approach.
Jun Qi –
This is the most advanced course covering the state of the art BERT techniques used in NLP.
Christopher Berry –
Exceptional course, James is an expert at NLP. Out of the numerous NLP courses I’ve done, this is the best one.
Deborishi Ganguly –
I left this rating because I am all about
Serge Sotnyk –
Strange exercises you can send a task once that is placed in a notebook. It has to be reviewed by other students. This is very wrong. Reviewing should be automatic (unit tests), it should be possible to send a lot of assignments otherwise, how do you learn new things? That said, the material is extremely actual, I learned new modern frameworks (e.g. Haystack). The author of the course has a good blog where I will still working over the articles, running and modifying the original code.